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Monitoring marine mammals is of broad interest to governments and individuals around the globe. Very high-resolution (VHR) satellites hold the promise of reaching remote and challenging locations to fill gaps in our knowledge of marine mammal distribution. The time has come to create an operational platform that leverages the increased resolution of satellite imagery, proof-of-concept research, advances in cloud computing, and machine learning to monitor the world's oceans. The Geospatial Artificial Intelligence for Animals (GAIA) initiative was formed to address this challenge with collaborative innovation from government agencies, academia, and the private sector. In this paper, we share lessons learned, challenges faced, and our vision for how VHR satellite imagery can enhance our understanding of cetacean distribution in the future. [ABSTRACT FROM AUTHOR]

Simple Summary: Due to climate change and human interference, many species are now without habitats and on the brink of extinction. Zoos and other conservation spaces allow for non-human animal preservation and public education about endangered species and ecosystems. Monitoring the health and well-being of animals in care, while providing species-specific environments, is critical for zoo and conservation staff. In order to best provide such care, keepers and researchers need to gather as much information as possible about individual animals and species as a whole. This paper focuses on existing technology to monitor animals, providing a review on the history of technology, including recent technological advancements and current limitations. Subsequently, we provide a brief introduction to our proposed novel computer software: an artificial intelligence software capable of unobtrusively and non-invasively tracking individuals' location, estimating position, and analyzing behaviour. This innovative technology is currently being trained with orangutans at the Toronto Zoo and will allow for mass data collection, permitting keepers and researchers to closely monitor individual animal welfare, learn about the variables impacting behaviour and provide additional enrichment or interventions accordingly. With many advancements, technologies are now capable of recording non-human animals' location, heart rate, and movement, often using a device that is physically attached to the monitored animals. However, to our knowledge, there is currently no technology that is able to do this unobtrusively and non-invasively. Here, we review the history of technology for use with animals, recent technological advancements, current limitations, and a brief introduction to our proposed novel software. Canadian tech mogul EAIGLE Inc. has developed an artificial intelligence (AI) software solution capable of determining where people and assets are within public places or attractions for operational intelligence, security, and health and safety applications. The solution also monitors individual temperatures to reduce the potential spread of COVID-19. This technology has been adapted for use at the Toronto Zoo, initiated with a focus on Sumatran orangutans (Pongo abelii) given the close physical similarity between orangutans and humans as great ape species. This technology will be capable of mass data collection, individual identification, pose estimation, behaviour monitoring and tracking orangutans' locations, in real time on a 24/7 basis, benefitting both zookeepers and researchers looking to review this information. [ABSTRACT FROM AUTHOR]

This paper addresses the question of how the brain of an animal achieves cognitive integration--that is to say how it manages to bring its fullest resources to bear on an ongoing situation. To fully exploit its cognitive resources, whether inherited or acquired through experience, it must be possible for unanticipated coalitions of brain processes to form. This facilitates the novel recombination of the elements of an existing behavioural repertoire, and thereby enables innovation. But in a system comprising massively many anatomically distributed assemblies of neurons, it is far from clear how such openended coalition formation is possible. The present paper draws on contemporary findings in brain connectivity and neurodynamics, as well as the literature of artificial intelligence, to outline a possible answer in terms of the brain's most richly connected and topologically central structures, its so-called connective core. [ABSTRACT FROM AUTHOR]

Even during its heyday, American behaviourist psychology was repeatedly criticized for the lack of diversity in its experimental subjects, with its almost exclusive focus on rats and pigeons. This paper revisits this debate by examining the rise and fall of a once promising alternative laboratory animal and model of intelligence, the raccoon. During the first two decades of the twentieth century, psychological investigations of the raccoon existed on the borderlands between laboratory experimentation, natural history and pet-keeping. Moreover, its chief advocate, Lawrence W. Cole, inhabited the institutional and geographic borderlands of the discipline. This liminality ultimately worked against the raccoon’s selection as a standardized model during the behaviourist era. The question of raccoon intelligence was also a prominent topic in the contemporaneous debates over the place of sentiment in popular nature writing. Although Cole and others argued that the raccoon provided unique opportunities to study mental attributes such as curiosity and attention, others accused the animal’s advocates of sentimentalism, anthropomorphism and nature faking. The paper examines the making and unmaking of this hybrid scientific culture as the lives of experimenters and animals became entangled. [ABSTRACT FROM AUTHOR]

Abstract Comparative research on the origins of human language often focuses on a limited number of language-related cognitive functions or anatomical structures that are compared across species. The underlying assumption of this approach is that a single or a limited number of factors may crucially explain how language appeared in the human lineage. Another potentially fruitful approach is to consider human language as the result of a (unique) assemblage of multiple cognitive and anatomical components, some of which are present in other species. This paper is a first step in that direction. It focuses on the baboon, a non-human primate that has been studied extensively for years, including several brain, anatomical, cognitive and cultural dimensions that are involved in human language. This paper presents recent data collected on baboons regarding (1) a selection of domain-general cognitive functions that are core functions for language, (2) vocal production, (3) gestural production and cerebral lateralization, and (4) cumulative culture. In all these domains, it shows that the baboons share with humans many cognitive or brain mechanisms which are central for language. Because of the multidimensionality of the knowledge accumulated on the baboon, that species is an excellent nonhuman primate model for the study of the evolutionary origins of language. [ABSTRACT FROM AUTHOR]

Relational cognition—the ability to infer relationships that generalize to novel combinations of objects—is fundamental to human and animal intelligence. Despite this importance, it remains unclear how relational cognition is implemented in the brain due in part to a lack of hypotheses and predictions at the levels of collective neural activity and behavior. Here we discovered, analyzed, and experimentally tested neural networks (NNs) that perform transitive inference (TI), a classic relational task (if A > B and B > C, then A > C). We found NNs that (i) generalized perfectly, despite lacking overt transitive structure prior to training, (ii) generalized when the task required working memory (WM), a capacity thought to be essential to inference in the brain, (iii) emergently expressed behaviors long observed in living subjects, in addition to a novel order-dependent behavior, and (iv) expressed different task solutions yielding alternative behavioral and neural predictions. Further, in a large-scale experiment, we found that human subjects performing WM-based TI showed behavior inconsistent with a class of NNs that characteristically expressed an intuitive task solution. These findings provide neural insights into a classical relational ability, with wider implications for how the brain realizes relational cognition. Author summary: The ability to infer underlying relationships in the world—or "relational cognition"—is fundamental to both human and animal intelligence. Despite this importance, it remains generally unknown how relational abilities are realized in the brain. Addressing this lack of knowledge requires generating testable hypotheses regarding the activity of neurons when relationships are inferred. In this study, we discovered artificial neural networks that perform transitive inference (TI), a classic relational task that has the form "if A > B and B > C, then A > C." We found that these neural networks show behavioral patterns that match those seen in humans and animals performing TI, and, further, performed TI in different ways, thereby providing different testable hypotheses regarding neural activity. We also conducted a large-scale behavioral study in humans, which suggested systematic differences in biological accuracy across the neural networks. These findings provide new hypotheses and insights regarding how TI, and relational abilities more generally, can be realized in the brain. [ABSTRACT FROM AUTHOR]

Knowledge of animal sentience is fundamental to many disciplines and imperative to the animal welfare movement. In this review, we examined what is being explored and discussed, regarding animal sentience, within the scientific literature. Rather than attempting to extract meaning from the many complex and abstract definitions of animal sentience, we searched over two decades of scientific literature using a peer-reviewed list of 174 keywords. The list consisted of human emotions, terminology associated with animal sentience, and traits often thought to be indicative of subjective states. We discovered that very little was actually being explored, and instead there was already much agreement about what animals can feel. Why then is there so much scepticism surrounding the science of animal sentience? Sentience refers to the subjective states of animals, and so is often thought to be impossible to measure objectively. However, when we consider that much of the research found to accept and utilise animal sentience is performed for the development of human drugs and treatment, it appears that measuring sentience is, after all, not quite as impossible as was previously thought. In this paper, we explored what has been published on animal sentience in the scientific literature and where the gaps in research lie. We drew conclusions on the implications for animal welfare science and argued for the importance of addressing these gaps in our knowledge. We found that there is a need for more research on positive emotional states in animals, and that there is still much to learn about taxa such as invertebrates. Such information will not only be useful in supporting and initiating legislative amendments but will help to increase understanding, and potentially positive actions and attitudes towards animals. [ABSTRACT FROM AUTHOR]

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Are there aspects of human intelligence that artificial intelligence cannot emulate? Harry Collins uses a distinction between tacit aspects of knowing, which cannot be digitized, and explicit aspects, which can be, to formulate an answer to this question. He postulates three purported areas of the tacit and argues that only "collective tacit knowing" cannot be adequately digitized. I argue, first, that Collins's approach rests upon problematic Cartesian assumptions—particularly his claim that animal knowing is strictly deterministic and, thus, radically different from human knowing. I offer evidence that human linguistic intelligence depends upon embodied forms of animal intelligence. Second, I suggest the development of deep-learning algorithms means that Collins's mimesis assumption (that successfully realized explicit instructions to machines are needed to confirm human-artificial intellectual equivalence) is no longer appropriate; equivalent accomplishment of goals is what counts (as he also concedes). However, persons must realize and integrate many goals and also deal with failures; a general-purpose AI capable of integrating all the needs and goals of human existence resists development. Third, I explain how Michael Polanyi's understanding of tacit knowing, quite different than Collins's concept of the tacit, exemplifies features that are missing in contemporary AI. I make use of evolutionary theory, studies of animal intelligence, biological insights, individual construction of meaning, and notions of human responsibility to argue for the existence of three categories that distinguish human from artificial intelligence. [ABSTRACT FROM AUTHOR]

Photovoltaic panels present an economical and environmentally friendly renewable energy solution, with advantages such as emission-free operation, low maintenance, and noiseless performance. However, their nonlinear power-voltage curves necessitate efficient operation at the Maximum Power Point (MPP). Various techniques, including Hill Climb algorithms, are commonly employed in the industry due to their simplicity and ease of implementation. Nonetheless, intelligent approaches like Particle Swarm Optimization (PSO) offer enhanced accuracy in tracking efficiency with reduced oscillations. The PSO algorithm, inspired by collective intelligence and animal swarm behavior, stands out as a promising solution due to its efficiency and ease of integration, relying only on standard current and voltage sensors commonly found in these systems, not like most intelligent techniques, which require additional modeling or sensoring, significantly increasing the cost of the installation. The primary contribution of this study lies in the implementation and validation of an advanced control system based on the PSO algorithm for real-time Maximum Power Point Tracking (MPPT) in a commercial photovoltaic system to assess its viability by testing it against the industry-standard controller, Perturbation and Observation (P&O), to highlight its advantages and limitations. Through rigorous experiments and comparisons with other methods, the proposed PSO-based control system's performance and feasibility have been thoroughly evaluated. A sensitivity analysis of the algorithm's search dynamics parameters has been conducted to identify the most effective combination for optimal real-time tracking. Notably, experimental comparisons with the P&O algorithm have revealed the PSO algorithm's remarkable ability to significantly reduce settling time up to threefold under similar conditions, resulting in a substantial decrease in energy losses during transient states from 31.96% with P&O to 9.72% with PSO. [ABSTRACT FROM AUTHOR]

The article discusses papers in the special issue of "Philosophical Transactions of the Royal Society B: Biological Sciences" devoted to cognition in animals, including a paper which proposes a cognitive architecture that can generate solutions to problems in the physical world in the case of a New Caledonian crow or a rook, and a paper offering an associative-cybernetic theory for associative learning in animals.

A traditional view of cognition is that it involves an internal process that represents, tracks or predicts an external process. This is not a general characteristic of all complex neural processing or feedback control, but rather implies specific forms of processing giving rise to specific behavioural capabilities. In this paper, I will review the evidence for such capabilities in insect navigation and learning. Do insects know where they are, or do they only know what to do? Do they learn what stimuli mean, or do they only learn how to behave? [ABSTRACT FROM AUTHOR]

When presented with structured sequences to learn, do nonhuman animals abstract and learn relational information-do they induce and learn rules? This paper provides an overview of the current evidence that bears on this question from our recent behavioral and psychobiological research on rat sequential learning. Evidence is presented that rats are sensitive to hierarchical structure in response sequences, that phrasing can bias rats' perception of pattern structure, that rats induce pattern structures from nonadjacent items in "interleaved" patterns, and that rule learning processes are active concurrently with other learning processes. The paper also describes work on the psychobiology of sequential learning that shows that multiple concurrent cognitive processes can be dissociated by MK-801, an NMDA receptor antagonist, and by other drug and lesion manipulations. Taken together, the results indicate that rats use rule learning processes concurrently with associative learning processes in a wide variety of sequential learning problems. [ABSTRACT FROM AUTHOR]

Current theory frames animal dispersal as an outcome of potentially complex, multi-factorial interactions and tradeoffs that may vary across individual, sex, rank, age, social group, species, habitat and time. Empirical data relevant to a broad range of the potential costs and benefits incurred by dispersal are, not surprisingly, limited for many mammals and other vertebrates. Here we present the first report on dispersal in a wild population of the Neotropical primate Saimiri sciureus (Primates: Cebidae). Long-term observations (1998-2001) of this squirrel monkey represent part of a broader study of the forest community at Raleighvallen in the Central Suriname Nature Reserve. These new dispersal records for S. sciureus are combined with comparable information from congeners, S. boliviensis in Peru and S. oerstedii in Costa Rica. The resulting three-way compilation includes the ecological, social and mating context for each congener. Further enhancing the inherent phylogenetic control of a within-genus comparison, these data were collected with the explicit intent of joint analyses, and the study sites for these small, arboreal social mammals are three of the least disturbed extant Neotropical forests in the historical record. Saimiri appears to merit description as the genus with the most diverse set of species dispersal patterns yet documented among mammals. (1) S. sciureus of both sexes undertake dispersal on several to many occasions during their lifetime. Females and immatures commonly transfer between troops. The large portion of male S. sciureus spend their adult years as solitary or peripheral males. Few males attain secure residence in a mixed-sex troop, a prerequisite for mating success. (2) On attainment of sexual maturity, male S. boliviensis emigrate with their same-age cohort, first joining all-male bands, and eventually entering mixed-sex troops with this same natal male birth cohort. Natal female S. boliviensis are philopatric and form cohesive matrilines. Within-troop competition determines each matriline's priority of access to fruit resources. (3) In contrast to both S. sciureus and S. boliviensis, S. oerstedii males are philopatric and maintain tight affiliation with same age-cohort males. Natal female S. oerstedii emigrate as juveniles prior to their first mating season, and may undertake secondary dispersals in subsequent years. Squirrel monkeys represent a genus with realistic prospects of discriminating the costs and benefits germane to species-typical dispersal strategies. To this end, we collate 30 different causal parameters commonly invoked as influencing mammalian dispersal patterns. Each of these factors is assessed separately for possible influence on the empirically determined sex and species differences. We predict the possible consequences of direct and inclusive fitness interactions on dispersal outcomes for future testing with genetic data. Components of Saimiri selective regimes particularly salient to female dispersal strategies include food competition, foraging benefits provided by kin and inbreeding avoidance. Dispersal patterns among male Saimiri are constrained by mate competition and the consequent reproductive skew, in addition to enhanced predation risk during dispersal forays. Little evidence, however, suggests that relative to familiar landscapes, exploitation of novel ranging areas substantially increases foraging costs or predation risk for dispersing squirrel monkeys of either sex. We then compare the species-specific dispersal regimes initially identified with the univariate array of proposed costs and benefits to the tradeoffs predicted by a selection of contemporary multivariate dispersal models. The multivariate models did not, however, improve substantially upon the collective insights on cost-benefit regimes achieved with the univariate hypotheses. Conclusions regarding the selective regimes structuring dispersal among squirrel monkeys are best considered provisional until genetic data become available allowing tests of our inferences concerning kin relationships and population structure of the study populations. In the end, this fine-grained analysis is consistent with contemporary understandings on the costs and benefits structuring dispersal strategies. Yet our findings provide an uncommonly clear demonstration that the outcome of the interaction of individual factors (food competition, mate competition, and inbreeding avoidance) depends in very subtle ways on the natural history of the organism. This text and two companion papers, II. Within-species and local variation and III. Cognition, comprise a monograph on the evolution and ecology of squirrel monkey dispersal patterns. Implications of the various results are relevant to resource and mate competition, inbreeding avoidance and kin-recognition, predation risk, coalition and alliance formation, cognitive capacities required for implementation of dispersal tactics, impacts of pre-Columbian anthropogenic disturbance on extant Neotropical biota, and conservation management, among others. [ABSTRACT FROM AUTHOR]

The process by which ant scouts move a group of nestmates toward a newly discovered food site is called recruitment. In this paper, I report on the interactions between scouts and nestmates that result in a graded recruitment response to graded food quality in the fire ant, Solenopsis invicta. Twelve experimental groups composed of 100 fire ant workers and 50 fire ant larvae were established (three experimental groups per colony × four stock colonies). Each experimental group was placed in a shallow, artificial nest with a glass cover. After a 48-h period of food deprivation, experimental groups were exposed to one of three concentrations of sugar water. Behavioral interactions between scouts and nestmates in each group were videotaped at 10× magnification for 20 min. Detailed behavioral data on a total of 120 scouts (10 scouts per experimental group) and ~1,000 nestmates (~90 nestmates per experimental group) were transcribed from the videotapes using standard play and frame-by-frame techniques. Throughout the recruitment process, scouts employed six discrete behaviors to inform nestmates of the location and quality of a food site. Scouts laid incoming trails, waggled their heads, increased walking tempo, stroked nestmates with their antennae, advertised with a brief food display, and led groups of nestmates to the food site by laying outgoing trails. In turn, nestmates assessed the food sample with antennae, then responded to or resisted recruitment based on the quality of food advertised, their employment status and their level of hunger. In summary, recruitment was an emergent property based on competent supply and demand decisions made face-to-face inside the nest rather than on the trail or at the food site. [ABSTRACT FROM AUTHOR]

In this paper, a comprehensive methodology and simulation framework will be reviewed, designed in order to study the emergence of adaptive and intelligent behavior in generic soft-bodied creatures. By incorporating artificial evolutionary and developmental processes, the system allows to evolve complete creatures (brain, body, developmental properties, sensory, control system, etc.) for different task environments. Whether the evolved creatures will resemble animals or plants is in general not known a priori, and depends on the specific task environment set up by the experimenter. In this regard, the system may offer a unique opportunity to explore differences and similarities between these two worlds. Different material properties can be simulated and optimized, from a continuum of soft/stiff materials, to the interconnection of heterogeneous structures, both found in animals and plants alike. The adopted genetic encoding and simulation environment are particularly suitable in order to evolve distributed sensory and control systems, which play a particularly important role in plants. After a general description of the system some case studies will be presented, focusing on the emergent properties of the evolved creatures. Particular emphasis will be on some unifying concepts that are thought to play an important role in the emergence of intelligent and adaptive behavior across both the animal and plant kingdoms, such as morphological computation and morphological developmental plasticity. Overall, with this paper, we hope to draw attention on set of tools, methodologies, ideas and results, which may be relevant to researchers interested in plant-inspired robotics and intelligence.

Environmental stressors can negatively affect avian cognitive abilities, potentially reducing fitness, for example by altering response to predators, display to mates, or memory of locations of food. We expand on current knowledge by investigating the effects of dietary mercury, a ubiquitous environmental pollutant and known neurotoxin, on avian cognition. Zebra finches Taeniopygia guttata were dosed for their entire lives with sub-lethal levels of mercury, at the environmentally relevant dose of 1.2 parts per million. In our first study, we compared the dosed birds with controls of the same age using tests of three cognitive abilities: spatial memory, inhibitory control, and color association. In the spatial memory assay, birds were tested on their ability to learn and remember the location of hidden food in their cage. The inhibitory control assay measured their ability to ignore visible but inaccessible food in favor of a learned behavior that provided the same reward. Finally, the color association task tested each bird's ability to associate a specific color with the presence of hidden food. Dietary mercury negatively affected spatial memory ability but not inhibitory control or color association. Our second study focused on three behavioral assays not tied to a specific skill or problem-solving: activity level, neophobia, and social dominance. Zebra finches exposed to dietary mercury throughout their lives were subordinate to, and more active than, control birds. We found no evidence that mercury exposure influenced our metric of neophobia. Together, these results suggest that sub-lethal exposure to environmental mercury selectively harms neurological pathways that control different cognitive abilities, with complex effects on behavior and fitness. [ABSTRACT FROM AUTHOR]

In this article, the paradigm of machine culture as an extension to machine intelligence is introduced. This new concept is modelled based on animal intelligence and culture. The example of orca intelligence and culture is considered as orcas possess in addition to skills allowing them to reach preys, the ability to transmit their culture from generation to generation. The orca intelligence is studied and then simulated to design an algorithm called Orca Algorithm (OA). OA consists in modelling the orca lifestyle and in particular the orcas social organization, echolocation behaviour and hunting techniques. In order to integrate the cultural dimension, OA was hybridized with the Cultural Algorithm (CA) to get an algorithm called Orca Cultural Algorithm (OCA). OCA was tested on 22 benchmark problems of the literature to evaluate its performance. Extensive experiments were first performed to set the algorithm parameters prior to measure its effectiveness and efficiency. In a second stage, OCA was adapted to discrete problems and applied to the maze game with four level of complexity. Additional experiments were held to compare the designed algorithm with recent state‐of‐the‐art evolutionary algorithms. The overall obtained results are very promising. [ABSTRACT FROM AUTHOR]

Some scientific researches have been conducted recently based on Artificial Intelligence (AI) to solve animal welfare and health related problems. However, no review study was conducted to assess the potential of AI in solving the diverse application problems in several animal species including ruminants, pig and poultry. To fill in this gap, this paper provides a systematic review on scientific research advancement in AI related animal farming based on 131 research publications over the past four decades. It was shown that the number of related studies has increased significantly since 2016, and the most intensive studies were focused on animal behavior detection and recognition, and concentrated mostly on farm animal species of pig (37.95%), cattle (37.44%), and poultry (16.92%); Also, most scientific research in animal farming driven by sensors and AI models were focused on data collection, processing, assessment, and analysis in the areas of animal behavior detection, disease monitoring, growth estimation, and environment monitoring at the experimental stage; Moreover, some technical challenges on AI like the accuracy and cost need to be improved before it could come into use in the commercial animal farming. [Display omitted] [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes Hyperspherical Acceleration Effect Particle Swarm Optimization (HAEPSO) for optimizing complex, multi-modal functions. The HAEPSO algorithm finds the particles that are trapped in deep local minima and accelerates them in the direction of global optima. This novel technique improves the efficiency by manipulating PSO parameters in hyperspherical coordinate system. Performance comparisons of HAEPSO are provided against different PSO variants on standard benchmark functions. Results indicate that the proposed algorithm gives robust results with good quality solution and faster convergence. The proposed algorithm is an effective technique for solving complex, higher dimensional multi-modal functions. [Copyright &y& Elsevier]

The intertwined processes of learning and evolution in complex environmental niches have resulted in a remarkable diversity of morphological forms. Moreover, many aspects of animal intelligence are deeply embodied in these evolved morphologies. However, the principles governing relations between environmental complexity, evolved morphology, and the learnability of intelligent control, remain elusive, because performing large-scale in silico experiments on evolution and learning is challenging. Here, we introduce Deep Evolutionary Reinforcement Learning (DERL): a computational framework which can evolve diverse agent morphologies to learn challenging locomotion and manipulation tasks in complex environments. Leveraging DERL we demonstrate several relations between environmental complexity, morphological intelligence and the learnability of control. First, environmental complexity fosters the evolution of morphological intelligence as quantified by the ability of a morphology to facilitate the learning of novel tasks. Second, we demonstrate a morphological Baldwin effect i.e., in our simulations evolution rapidly selects morphologies that learn faster, thereby enabling behaviors learned late in the lifetime of early ancestors to be expressed early in the descendants lifetime. Third, we suggest a mechanistic basis for the above relationships through the evolution of morphologies that are more physically stable and energy efficient, and can therefore facilitate learning and control. The authors propose a new framework, deep evolutionary reinforcement learning, evolves agents with diverse morphologies to learn hard locomotion and manipulation tasks in complex environments, and reveals insights into relations between environmental physics, embodied intelligence, and the evolution of rapid learning. [ABSTRACT FROM AUTHOR]

Culture has traditionally been attributed only to human beings. Despite growing evidence of behavioral diversity in wild chimpanzee populations, most anthropologists and psychologists still deny culture to this animal species. We argue here that culture is not monolithic but a set of processes. These processes show much diversity both in the social norms and models that determine which individuals will be exposed to particular cultural variants and what cultural variants will be present in the population and in the social learning mechanisms that determine the fidelity of transmission of the variants over time. Recognition of the diversity of these processes is important because it affects cultural dissemination, cultural evolution, and the complexity of cultural artifacts. A comparison of chimpanzee and human cultures shows many deep similarities, thus suggesting that they share evolutionary roots. Two possible differences between the two species are discussed. First, thanks to indirect means of transmission such as language, cultural dissemination is possible over greater stretches of time and space in humans than in chimpanzees. Second, human cultures rely more intensively than chimpanzee cultures on cumulative cultural evolution through the ratchet effect, which allows the accumulation of modifications over time and produces more elaborate cultural artifacts. [ABSTRACT FROM AUTHOR]

The article discusses cognitive scientist Marc Hauser and an investigation of his research being conducted by Harvard University. The insights on animal cognition derived from Hauser's 30 years of research are discussed. Once-held notions of human uniqueness are said to have been diminished by Hauser's findings. Hauser also is noted for his work and written and public communications regarding morality and its evolutionary roots. Questions have been raised about many research papers coauthored by Hauser and a paper he coauthored in a 2002 issue of "Cognition" was retracted.

The hypothesis proposed by Macphail (1987) is that differences in intelligent behavior thought to distinguish different species were likely attributed to differences in the context of the tasks being used. Once one corrects for differences in sensory input, motor output, and incentive, it is likely that all vertebrate animals have comparable intellectual abilities. In the present article I suggest a number of tests of this hypothesis with pigeons. In each case, the evidence suggests that either there is evidence for the cognitive behavior, or the pigeons suffer from biases similar to those of humans. Thus, Macphail's hypothesis offers a challenge to researchers to find the appropriate conditions to bring out in the animal the cognitive ability being tested. [ABSTRACT FROM AUTHOR]

Kant makes the double assumption that the separate, completely independent contributions of Reason (or thought) and passively received "sensory impressions" (or sensibility) must, somehow, mesh correctly if it is to yield empirical cognition; and that, at the same time, Vernunft must already possess the requisite concepts and categories before and entirely independently of the sensory event itself. Kant invents Vernunft as the decisive "faculty of cognition", but it fails utterly. Joseph Margolis I. 1 There is no easy way to defeat Kant's first Critique: Kant is indefatigable in rescuing his apparent lapses by means of overriding second thoughts and ingenuities. Kant introduces Reason (Vernunft) as the executive (transcendental) "faculty of cognition" possessed exclusively by enlanguaged selves. [Extracted from the article]

After re-reading Macphail's (1987) essay "The Comparative Psychology of Intelligence" with all the associated commentaries, I was struck by how contemporary many of the arguments and counter-arguments still appear. Of course, we now know much more about the abilities of many more species (including their neurobiology) and fewer researchers currently favor explanations of behavior based solely on associative processes; however, the role of contextual variables in comparative psychology still remains cloudy. I discuss these issues briefly. Given my research interests involving the cognitive and communicative abilities of Grey parrots, the one aspect of the original article upon which I feel I can comment in depth involves Macphail's claims about the importance of language—and specifically syntax—in problem-solving and thus in placing humans above all other creatures. Granted, no other species has (or in my opinion is likely ever to acquire) everything that goes into what is considered "human language." Nevertheless, several other species have acquired symbolic representation, and considerable information now exists upon which to base an argument that such acquisition by itself enables more complex and "human-like" cognitive processes. Such processes may form the basis of the kind of intelligence that is measured—not surprisingly—with human-based tasks, including the use of such representations as a means to directly query non-human subjects in ways not unlike those used with young children. [ABSTRACT FROM AUTHOR]

The author comments on an article by Neeltje J. Boogert et al about mate choice for cognitive traits in animals. She agrees with the point of the study authors that female choice for cognition will be hard to disentangle from choice for enhanced condition on the basis of correlated indicator traits. She mentions some predictions that arise if female evaluation of male displays is experience dependent. She also suggests that the paper should include studying why different females take different decisions.

Presents the authors' views about the comments on their paper "Do Dogs Resemble Their Owners?" Information about the methodology used in the study; Remarks on the non-independence of ratings used in the original study; Information about a different method of data collection that avoids the non-independence issue; Comments on the results obtained by using the new method of data collection.

Object recognition is central to perception and cognition. Yet relatively little is known about the environmental factors that cause invariant object recognition to emerge in the newborn brain. Is this ability a hardwired property of vision? Or does the development of invariant object recognition require experience with a particular kind of visual environment? Here, we used a high-throughput controlled-rearing method to examine whether newborn chicks (Gallus gallus) require visual experience with slowly changing objects to develop invariant object recognition abilities. When newborn chicks were raised with a slowly rotating virtual object, the chicks built invariant object representations that generalized across novel viewpoints and rotation speeds. In contrast, when newborn chicks were raised with a virtual object that rotated more quickly, the chicks built viewpoint-specific object representations that failed to generalize to novel viewpoints and rotation speeds. Moreover, there was a direct relationship between the speed of the object and the amount of invariance in the chick's object representation. Thus, visual experience with slowly changing objects plays a critical role in the development of invariant object recognition. These results indicate that invariant object recognition is not a hardwired property of vision, but is learned rapidly when newborns encounter a slowly changing visual world. [ABSTRACT FROM AUTHOR]

In birds and primates, the frequency of behavioural innovation has been shown to covary with absolute and relative brain size, leading to the suggestion that large brains allow animals to innovate, and/or that selection for innovativeness, together with social learning, may have driven brain enlargement. We examined the relationship between primate brain size and both technical (i.e. tool using) and non-technical innovation, deploying a combination of phylogenetically informed regression and exploratory causal graph analyses. Regression analyses revealed that absolute and relative brain size correlated positively with technical innovation, and exhibited consistently weaker, but still positive, relationships with non-technical innovation. These findings mirror similar results in birds. Our exploratory causal graph analyses suggested that technical innovation shares strong direct relationships with brain size, body size, social learning rate and social group size, whereas non-technical innovation did not exhibit a direct relationship with brain size. Nonetheless, non-technical innovation was linked to brain size indirectly via diet and life-history variables. Our findings support 'technical intelligence' hypotheses in linking technical innovation to encephalization in the restricted set of primate lineages where technical innovation has been reported. Our findings also provide support for a broad co-evolving complex of brain, behaviour, life-history, social and dietary variables, providing secondary support for social and ecological intelligence hypotheses. The ability to gain access to difficult- to-extract, but potentially nutrient-rich, resources through tool use may have conferred on some primates adaptive advantages, leading to selection for brain circuitry that underlies technical proficiency. [ABSTRACT FROM AUTHOR]

The primate brain intelligently processes visual information from the world as the eyes move constantly. The brain must take into account visual motion induced by eye movements, so that visual information about the outside world can be recovered. Certain neurons in the dorsal part of monkey medial superior temporal area (MSTd) play an important role in integrating information about eye movements and visual motion. When a monkey tracks a moving target with its eyes, these neurons respond to visual motion as well as to smooth pursuit eye movements. Furthermore, the responses of some MSTd neurons to the motion of objects in the world are very similar during pursuit and during fixation, even though the visual information on the retina is altered by the pursuit eye movement. We call these neurons compensatory pursuit neurons. In this study we develop a computational model of MSTd compensatory pursuit neurons based on physiological data from single unit studies. Our model MSTd neurons can simulate the velocity tuning of monkey MSTd neurons. The model MSTd neurons also show the pursuit compensation property. We find that pursuit compensation can be achieved by divisive interaction between signals coding eye movements and signals coding visual motion. The model generates two implications that can be tested in future experiments: (1) compensatory pursuit neurons in MSTd should have the same direction preference for pursuit and retinal visual motion; (2) there should be non-compensatory pursuit neurons that show opposite preferred directions of pursuit and retinal visual motion. [ABSTRACT FROM AUTHOR]

Simple Summary: It is difficult to measure animal intelligence because the definition of 'intelligence' varies, and many animals are good at specific tasks used to measure intelligence or cognition. To address this, scientists often look for evidence of common cognitive abilities. One such ability, the ability to learn concepts, is thought to be rare in animals, especially invertebrates. Concepts include the ideas of 'same' and 'different'. These concepts can be applied to anything in the environment while also being independent of those objects and can help animals understand and survive their environment. Amblypygids, a relative of spiders, live in tropical and subtropical areas, are very good learners, and have a large, complex brain region known to process information from multiple senses. We tested whether amblypygids could learn the concept of 'same' by training them to move toward a stimulus that matched with an initial stimulus. We also trained some individuals to learn the concept 'different' by training them to move toward a non-matching stimulus. When we used new stimuli, the amblypygids did not move toward the correct stimulus significantly more often than the incorrect stimulus, suggesting either they are unable to learn these higher-order concepts or our experimental design failed to elicit that ability. Comparative cognition aims to understand the evolutionary history and current function of cognitive abilities in a variety of species with diverse natural histories. One characteristic often attributed to higher cognitive abilities is higher-order conceptual learning, such as the ability to learn concepts independent of stimuli—e.g., 'same' or 'different'. Conceptual learning has been documented in honeybees and a number of vertebrates. Amblypygids, nocturnal enigmatic arachnids, are good candidates for higher-order learning because they are excellent associational learners, exceptional navigators, and they have large, highly folded mushroom bodies, which are brain regions known to be involved in learning and memory in insects. In Experiment 1, we investigate if the amblypygid Phrynus marginimaculatus can learn the concept of same with a delayed odor matching task. In Experiment 2, we test if Paraphrynus laevifrons can learn same/different with delayed tactile matching and nonmatching tasks before testing if they can transfer this learning to a novel cross-modal odor stimulus. Our data provide no evidence of conceptual learning in amblypygids, but more solid conclusions will require the use of alternative experimental designs to ensure our negative results are not simply a consequence of the designs we employed. [ABSTRACT FROM AUTHOR]

Larval zebrafish possess several experimental advantages for investigating the molecular and neural bases of learning and memory. Despite this, neuroscientists have only recently begun to use these animals to study memory. However, in a relatively short period of time a number of forms of learning have been described in zebrafish larvae, and significant progress has been made toward their understanding. Here we provide a comprehensive review of this progress; we also describe several promising new experimental technologies currently being used in larval zebrafish that are likely to contribute major insights into the processes that underlie learning and memory. [ABSTRACT FROM AUTHOR]

Neural conditioning associates cues and actions with following rewards. The environments in which robots operate, however, are pervaded by a variety of disturbing stimuli and uncertain timing. In particular, variable reward delays make it difficult to reconstruct which previous actions are responsible for following rewards. Such an uncertainty is handled by biological neural networks, but represents a challenge for computational models, suggesting the lack of a satisfactory theory for robotic neural conditioning. The present study demonstrates the use of rare neural correlations in making correct associations between rewards and previous cues or actions. Rare correlations are functional in selecting sparse synapses to be eligible for later weight updates if a reward occurs. The repetition of this process singles out the associating and reward-triggering pathways, and thereby copes with distal rewards. The neural network displays macro-level classical and operant conditioning, which is demonstrated in an interactive real-life human-robot interaction. The proposed mechanism models realistic conditioning in humans and animals and implements similar behaviors in neuro-robotic platforms. [ABSTRACT FROM AUTHOR]

Animal cognition experiments frequently reveal striking individual variation but rarely consider its causes and largely ignore its potential consequences. Studies often focus on a subset of high-performing subjects, sometimes viewing evidence from a single individual as sufficient to demonstrate the cognitive capacity of a species. We argue that the emphasis on demonstrating species-level cognitive capacities detracts from the value of individual variation in understanding cognitive development and evolution. We consider developmental and evolutionary interpretations of individual variation and use metaanalyses of data from published studies to examine predictors of individual performance. We show that reliance on small sample sizes precludes robust conclusions about individual abilities as well as inter- and intraspecific differences. We advocate standardization of experimental protocols and pooling of data between laboratories to improve statistical rigour. Our analyses show that cognitive performance is influenced by age, sex, rearing conditions and previous experience. These effects limit the validity of comparative analyses unless developmental histories are taken into account, and complicate attempts to understand how cognitive traits are expressed and selected under natural conditions. Further understanding of cognitive evolution requires efforts to elucidate the heritability of cognitive traits and establish whether elevated cognitive performance confers fitness advantages in nature. [ABSTRACT FROM AUTHOR]

With the exception of a few model species, individual differences in cognition remain relatively unstudied in non-human animals. One intriguing possibility is that variation in cognition is functionally related to variation in personality. Here, we review some examples and present hypotheses on relationships between personality (or behavioural syndromes) and individual differences in cognitive style. Our hypotheses are based largely on a connection between fast--slow behavioural types (BTs; e.g. boldness, aggressiveness, exploration tendency) and cognitive speed--accuracy trade-offs. We also discuss connections between BTs, cognition and ecologically important aspects of decision-making, including sampling, impulsivity, risk sensitivity and choosiness. Finally, we introduce the notion of cognition syndromes, and apply ideas from theories on adaptive behavioural syndromes to generate predictions on cognition syndromes. [ABSTRACT FROM AUTHOR]

Differences between individuals are the raw material from which theories of the evolution and ontogeny of cognition are built. For example, when 4-year-old children pass a test requiring them to communicate the content of another's falsely held belief, while 3-year-olds fail, we know that something must change over the course of the third year of life. In the search for what develops or evolves, the typical route is to probe the extents and limits of successful individuals' ability. Another is to focus on those that failed, and find out what difference or lack prevented them from passing the task. Recent research in developmental psychology has harnessed individual differences to illuminate the cognitive mechanisms that emerge to enable success. We apply this approach to explaining some of the failures made by chimpanzees when using tools to solve problems. Twelve of 16 chimpanzees failed to discriminate between a complete and a broken tool when, after being set down, the ends of the broken one were aligned in front of them. There was a correlation between performance on this aligned task and another in which after being set down, the centre of both tools was covered, suggesting that the limiting factor was not the representation of connection, but memory or attention. Some chimpanzees that passed the aligned task passed a task in which the location of the broken tool was never visible but had to be inferred. [ABSTRACT FROM AUTHOR]

Do we fully understand the structure of the problems we present to our subjects in experiments on animal cognition, and the information required to solve them? While we currently have a good understanding of the behavioural and neurobiological mechanisms underlying associative learning processes, we understand much less about the mechanisms underlying more complex forms of cognition in animals. In this study, we present a proposal for a new way of thinking about animal cognition experiments. We describe a process in which a physical cognition task domain can be decomposed into its component parts, and models constructed to represent both the causal events of the domain and the information available to the agent. We then implement a simple set of models, using the planning language MAPL within the MAPSIM simulation environment, and applying it to a puzzle tube task previously presented to orangutans. We discuss the results of the models and compare them with the results from the experiments with orangutans, describing the advantages of this approach, and the ways in which it could be extended. [ABSTRACT FROM AUTHOR]

A fundamental question concerning group-living species is what factors influence the evolution of sociality. Although several studies link adult social bonds to fitness, social patterns and relationships are often formed early in life and are also likely to have fitness consequences, particularly in species with lengthy developmental periods, extensive social learning, and early social bond-formation. In a longitudinal study of bottlenose dolphins (Tursiops sp.), calf social network structure, specifically the metric eigenvector centrality, predicted juvenile survival in males. Additionally, male calves that died post- weaning had stronger ties to juvenile males than surviving male calves, suggesting that juvenile males impose fitness costs on their younger counterparts. Our study indicates that selection is acting on social traits early in life and highlights the need to examine the costs and benefits of social bonds during formative life history stages. [ABSTRACT FROM AUTHOR]

The article focuses on a study which aims at assessing visual and olfactory associative learning in Anopheles (An.) gambiae, the malaria causing vector in Africa. In the study, various experiments were conducted and behavioral assays were developed to understand and describe the occurrence and processes of associative learning in An. gambiae. It shows high associative visual and olfactory learning in female An. gambiae in host finding and concludes knowledge gap in the mosquito's ecology.

New Caledonian crows were presented with Bird and Emery's (2009a) Aesop's fable paradigm, which requires stones to be dropped into a water-filled tube to bring floating food within reach. The crows did not spontaneously use stones as tools, but quickly learned to do so, and to choose objects and materials with functional properties. Some crows discarded both inefficient and non-functional objects before observing their effects on the water level. Interestingly, the crows did not learn to discriminate between functional and non-functional objects and materials when there was an arbitrary, rather than causal, link between object and reward. This finding suggests that the crows' performances were not based on associative learning alone. That is, learning was not guided solely by the covariation rate between stimuli and outcomes or the conditioned reinforcement properties acquired by functional objects. Our results, therefore, show that New Caledonian crows can process causal information not only when it is linked to sticks and stick-like tools but also when it concerns the functional properties of novel types of tool. [ABSTRACT FROM AUTHOR]