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Inductive reasoning is a core cognitive process of fluid intelligence, predicting a variety of educational outcomes. The Cognitive Training for Children (CTC) program is an educational intervention designed to develop children's inductive reasoning skills, with previous investigations finding substantial effects of the program on both inductive reasoning ability and classroom learning. The present study assessed both individual and small-group CTC training against a no-treatment control condition to investigate the effects on inductive and deductive reasoning and mathematics achievement in a primary school-aged Australian cohort. Students who received individual training outperformed those in the control condition on measures of inductive and deductive reasoning, and those in the small-group condition also outperformed the control condition on a measure of inductive reasoning 3 months following training. However, hypotheses regarding transfer effects to mathematics achievement were not supported. Directions for future research, focusing on extended longitudinal studies and motivational variables, are discussed.

Starting from John MacFarlane's recent survey of answers to the question ‘What is assertion?’, I defend an account of assertion that draws on elements of MacFarlane's and Robert Brandom's commitment accounts, Timothy Williamson's knowledge norm account, and my own previous work on the normative status of logic. I defend the knowledge norm from recent attacks. Indicative conditionals, however, pose a problem when read along the lines of Ernest Adams' account, an account supported by much work in the psychology of reasoning. Furthermore, there seems to be no place for degrees of belief in the accounts of belief and assertion given here. Degrees of belief do have a role in decision-making, but, again, there is much evidence that the orthodox theory of subjective utility maximization is not a good description of what we do in decision-making and, arguably, neither is it a good normative guide to how we ought to make decisions.

International audience; In "Mercier and Sperber's Argumentative Theory of Reasoning: From Psychology of Reasoning to Argumentation Studies" (2012) Cristian Santibáñez Yañez offers an interesting take on a new theory of reasoning put forward by Dan Sperber and myself. 1 His comments are especially interesting since they come from the perspective of argumentation studies ("traditionally dialectics, rhetoric and (informal) logic," 155), a field that Santibáñez Yañez contends has been neglected in this novel theory. After very briefly summarizing the main idea of the argumentative theory of reasoning and clarifying some points for which Santibáñez Yañez may not be offering an entirely accurate representation, the present article will offer a suggestion regarding the potential for mutual enrichment between argumentation studies and the argumentative theory of reasoning.

For a methodology of economics journal, one of the most important things to emphasize about Amartya Sen's The Idea of Justice is the priority it gives to methodological reasoning in its approach to...

This paper presents an adaptive logic enhancement of conditional logics of normality that allows for defeasible applications of Modus Ponens to conditionals. In addition to the possibilities these logics already offer in terms of reasoning about conditionals, this way they are enriched by the ability to perform default inferencing. The idea is to apply Modus Ponens defeasibly to a conditional and a fact on the condition that it is ‘safe' to do so concerning the factual and conditional knowledge at hand. It is for instance not safe if the given information describes exceptional circumstances: although birds usually fly, penguins are exceptional to this rule. The two adaptive standard strategies are shown to correspond to different intuitions, a skeptical and a credulous reasoning type, which manifest themselves in the handling of so-called floating conclusions.

In common with a number of other authors I believe that there has been a paradigm shift in the psychology of reasoning, specifically the area traditionally labelled as the study of deduction. The deduction paradigm was founded in a philosophical tradition that assumed logicality as the basis for rational thought, and provided binary propositional logic as the agreed normative framework. By contrast, many contemporary authors assume that people have degrees of uncertainty in both premises and conclusions, and reject binary logic as a workable normative system. I discuss a number of questions and challenges for this new psychology of reasoning, including the following: (a) Do we need an alternative normative system, such as Bayesianism, for the new paradigm? (b) Is there any longer a clear distinction between the study of deductive and inductive reasoning, the latter having its own tradition and literature? (c) Precisely how is the integrated study of reasoning and decision making facilitated by the new par...

A common view in philosophy is that the way human beings reason is not only gradually better, but that our way of reasoning is fundamentally distinctive. Findings in the psychology of reasoning challenge the traditional view according to which human beings reason in accordance with the laws of logic and probability theory, but rather suggest that human reasoning consists in the application of domain specific rules of thumb similar to those that we ascribe to some intelligent non-human animals as well. However, this view on human reasoning is unable to explain human accomplishments like technological innovations or scientific progress. David Papineau offers a theory of human theoretical rationality that is consistent with the psychological view on human reasoning but that can also explain how humans sometimes are able to transcend the limitations of their biologically quick and dirty modes of thought and thereby reach a high level of accuracy. Papineau claims that the abilities that constitute theoretical rationality are unique to the human species and thus, that human reasoning is fundamentally distinctive after all. In this paper I am going to discuss to what extent these abilities in fact are unique to our species and whether this theoretical rationality can be called an anthropological difference.

Robots operating in a complex human-inhabited environment need to represent and reason about different kinds of knowledge, including ontological, spatial, causal, temporal and resource knowledge. Often, these reasoning tasks are not mutually independent, but need to be integrated with each other. Integrated reasoning is especially important when dealing with knowledge derived from perception, which may be intrinsically incomplete or ambiguous. For instance, the non-observable property that a dish has been used and should therefore be washed can be inferred from the observable properties that it was full before and that it is empty now. In this paper, we present a hybrid reasoning framework which allows to easily integrate different kinds of reasoners. We demonstrate the suitability of our approach by integrating two kinds of reasoners, for ontological reasoning and for temporal reasoning, and using them to recognize temporally and ontologically defined object properties in point cloud data captured using an RGB-D camera.

Characterizing the modes of reasoning typically applied by students to solve different types of chemistry problems is of central importance for the design of instructional strategies that can better support their learning of specific content. Thus, the central goal of this study was to identify dominant modes of reasoning expressed by college chemistry students while working in self-initiated study groups. We were particularly interested in exploring potential relationships between modes of reasoning, content focus of group discussions, and levels of cognitive processing. Our study was based on the analysis of student conversations in 34 study sessions of 14 study groups involving over 100 students enrolled in the first semester of college organic chemistry. Our analysis indicated that most of the content-related conversations in the study could be categorized as involving at least one of four major reasoning modes: Model-based reasoning, case-based reasoning, rule-based reasoning, and symbol-based reasoning. In general, group talk was largely focused on issues of representation and structure which preferentially invoked rule-based reasoning; discussions about chemical reactions heavily relied on case-based reasoning. Overall, model-based reasoning was minimally applied. In general, over 70% of the content-related conversations corresponded to lower levels of cognitive processing. Rule-based thinking and case-based thinking were often based on students remembering and applying knowledge. Although model-based reasoning was used scarcely, it more frequently led to higher levels of cognitive processing. The results of our work provide insights into how to modify instruction to better support students' reasoning inside and outside the classroom.

The paper proposes a multi-viewpoint system to support human abductive reasoning for diagnosis, prognosis and trial-and-error activities for supervising automated systems. This multi-viewpoint approach interprets the same set of events from the different viewpoints in this set. The algorithms for managing these viewpoints and the set of events are related to hypothetical reasoning, and they use several main functions to (1) select or reject certain events, (2) cancel or recover these events, and (3) manage the consistency of the viewpoints. This approach is applied to diagnosis and trial-and-error activities related to the phone troubleshooting problem.

We propose a critique ofnormativism, defined as the idea that human thinking reflects a normative system against which it should be measured and judged. We analyze the methodological problems associated with normativism, proposing that it invites the controversial “is-ought” inference, much contested in the philosophical literature. This problem is triggered when there are competing normative accounts (the arbitration problem), as empirical evidence can help arbitrate between descriptive theories, but not between normative systems. Drawing on linguistics as a model, we propose that a clear distinction between normative systems and competence theories is essential, arguing that equating them invites an “is-ought” inference: to wit, supporting normative “ought” theories with empirical “is” evidence. We analyze in detail two research programmes with normativist features – Oaksford and Chater's rational analysis and Stanovich and West's individual differences approach – demonstrating how, in each case, equating norm and competence leads to an is-ought inference. Normativism triggers a host of research biases in the psychology of reasoning and decision making: focusing on untrained participants and novel problems, analyzing psychological processes in terms of their normative correlates, and neglecting philosophically significant paradigms when they do not supply clear standards for normative judgement. For example, in a dual-process framework, normativism can lead to a fallacious “ought-is” inference, in which normative responses are taken as diagnostic of analytic reasoning. We propose that little can be gained from normativism that cannot be achieved by descriptivist computational-level analysis, illustrating our position with Hypothetical Thinking Theory and the theory of the suppositional conditional. We conclude that descriptivism is a viable option, and that theories of higher mental processing would be better off freed from normative considerations.

Deductive reasoning is an essential part of complex cognition. It occurs whenever human beings (or machines) draw conclusions that go beyond what is explicitly provided. Reasoning about spatial relations is an excellent testbed for the assessment of competing reasoning theories. In the present paper we show that such competing theories are often less diverse than one might think. We introduce an approach for how relational reasoning can be conceived as verbal reasoning. We describe a theory of how humans construct a one-dimensional mental representation given spatial relations. In this construction process objects are inserted in a dynamic structure called a ''queue'' which provides an implicit direction. The spatial interpretation of this direction can theoretically be chosen freely. This implies that choices in the process of constructing a mental representation influence the result of deductive spatial reasoning. To derive the precise rules for the construction process we employ the assumption that humans try to minimize their cognitive effort, and two cost measures are compared to judge the efficiency of the construction process. From this we deduce how the queue should be constructed. We discuss empirical evidence for this approach and provide algorithms for a computational implementation of the construction and reasoning process.

The existence of general-purpose cognitive mechanisms related to intelligence, which appear to facilitate all forms of problem solving, conflicts with the strong modularity view of the mind espoused by some evolutionary psychologists. The current study assessed the contribution of general intelligence (g) to explaining variation in contextualized deductive reasoning. One hundred and twelve participants solved 70 contextualized reasoning problems in a computerized version of the Wason Card Selection Task that recorded both accuracy and reaction time. Consistent with prior research, in the sample as a whole, precautionary and social exchange reasoning problems were solved more frequently and more quickly than reasoning problems about arbitrary rules. At the individual-differences level of analysis, however, performance on all reasoning tests was significantly correlated and loaded on a single deductive-reasoning accuracy factor. Further, this factor was significantly correlated with g. There was no relation, however, between g and the speed of arriving at the correct answer for any form of deductive reasoning. We discuss the implications of these findings for evolutionary psychology, intelligence, and reasoning.

We study the accomplishment of the abstract version of Wason’s selection task in a cooperative dialogue context that has been neglected in the research devoted to this task. 123 psychology students, 75 in their third year and 48 in their first year of studies participated in the experiment. 59 students performed the task individually (control group) and 32 in dyads (experimental group) while we recorded their dialogues. In accordance with the literature, the dyads outperform significantly the students working alone. To discover the strategies implemented in the four dyads which succeeded, we analyzed their respective dialogues with a theory (‘Interlocutory Logic’) of the logical form of conversational events as they are manifested phenomenally in natural language. We show that these strategies are situated and emergent products of the dialogue, since no member of the dyads knew them before the interaction. So, it is surely by supporting the emergence of such joint cognition that the interaction is a factor of cognitive progress. We conclude this research by some remarks on the Wason’s task and moreover on the methodological solipsism in the psychology of reasoning.

Having defended the usefulness of our definition of reasoning, we stress that reasoning is not only for convincing but also for evaluating arguments, and that as such it has an epistemic function. We defend the evidence supporting the theory against several challenges: People are good informal arguers, they reason better in groups, and they have a confirmation bias. Finally, we consider possible extensions, first in terms of process-level theories of reasoning, and second in the effects of reasoning outside the lab.

Case-based reasoning is a familiar method of evaluating sentences. But when applied to conditionals, it seems to lead to implausible conclusions. In this paper I argue that the problem arises from equating the probability of a conditional sentence on the evidential supposition of some condition with the conditional probability of the former, given the latter.

— This article reviews recent evidence for the claim that infants possess a theory of mind. Two conceptual systems (CS) of psychological reasoning are distinguished: CS1, underlying the attribution of motivational states such as goals and dispositions, and CS2, supporting a representational theory of mind, that is, an understanding of false belief. There is ample evidence for CS1 even in the 1st year of life, whereas the claim that CS2 is operational in infancy is controversial. The article proposes a lean interpretation of findings on infants’ representation of false belief that assumes that a fast and automatic, but limited and inflexible, social information processing system guides infants’ encoding of belief-based intentional action.

One of the main tenets of the mental model theory is that when individuals reason, they think about possibilities. According to this theory, reasoning on what is possible from the truth of a sentence would be psychologically basic, whereas reasoning the other way round, on the truth or falsity of a sentence from a given state of affairs, would require some meta-ability. The present study tested the developmental corollary of this theory, which is that reasoning about possibilities should develop first, whereas the development of reasoning about truth-value should be delayed. For this purpose, 3rd, 6th, and 9th graders as well as adults were presented with tasks requiring them to evaluate either the possibilities compatible with conditional sentences or the truth-value of these sentences from these same possibilities. The results revealed 2 phenomena. First, the same developmental trend was observed in both tasks with 3 successive interpretational levels: conjunctive, biconditional, and then conditional. Second, there was a developmental lag between the 2 forms of reasoning--with developmental transitions from one level to the next occurring about 3 years later when reasoning about truth-value. The implications of these results for theories of cognitive development and of reasoning are discussed.

This chapter focuses on reasoning about the causal explanation of events and human activities that are indeterminate and complex. We first consider some classical ideas about physical causation from David Hume and John Stuart Mill, who had significant impact on the psychology of reasoning, and we find in their writings some notions that carry over into modern analyses of cause-effect relations and causal reasoning. We then present the macrocognition paradigm, which is empirically grounded in studies of naturalistic decision making, and approaches the analysis of causal reasoning through investigation of the functional purposes of various forms of causal reasoning. This sets the stage for presentation of our research on how people interpret the causal reasoning that is presented in newspaper articles. Findings include new patterns and models of causal reasoning. We conclude with a discussion of some "myths" about causation that characterize theories but that do not match well to our research findings.

reasoning refers to the ability to reason logically with premises that do not allow reference to knowledge about the real world. This form of reasoning is complex and difficult, and at the same time, it is critical for understanding science and mathematics. Two studies examined the use of analogy as a method to bridge reasoning with familiar content and abstract reasoning among older adolescents. The results showed that the ability to make an appropriate analogy depends on reasoning ability. Neither of the two procedures used resulted in an improvement in abstract reasoning. However, generating an inappropriate analogy actually decreased abstract reasoning performance among students who showed greater initial levels of reasoning ability. These results highlight the problems associated with using familiar reasoning as a basis for learning abstract reasoning skills.

We argue that reasoning has been conceptualized so narrowly in what is known as 'psychology of reasoning' that reasoning's relevance to cognitive science has become well-nigh invisible. Reasoning is identified with determining whether a conclusion follows validly from given premises, where 'valid' is taken to mean 'valid according to classical logic'. We show that there are other ways to conceptualize reasoning, more in line with current logical theorizing, which give it a role in psychological processes ranging from (verbal) discourse comprehension to (nonverbal) planning. En route we show that formal logic, at present marginalized in cognitive science, can be an extremely valuable modeling tool. In particular, there are cases in which probabilistic modeling must fail, whereas logical models do well. WIREs Cogni Sci 2011 2 555-567 DOI: 10.1002/wcs.134 For further resources related to this article, please visit the WIREs website.

This paper describes the problem of doing description logic (DL) reasoning with partially closed world. The issue was addressed by extending the syntax of DL SROIQ with an NBox, which specifies the predicates to close, extending the semantics with the idea of negation as failure, reducing the closed world reasoning to incremental reasoning on classical DL ontologies, and applying the syntactic approximation technology to improve the reasoning performance. Compared with the existing DBox approach, which corresponds to the relation database, the NBox approach supports deduction on closed concepts and roles. Also, the approximate reasoning can reduce reasoning complexity from N2EXPTIME-complete to PTIME-complete while preserving the correctness of reasoning for ontologies with certain properties.

Reports that infants in the second year of life can attribute false beliefs to others have all used a search paradigm in which an agent with a false belief about an object's location searches for the object. The present research asked whether 18-month-olds would still demonstrate false-belief understanding when tested with a novel non-search paradigm. An experimenter shook an object, demonstrating that it rattled, and then asked an agent, "Can you do it?" In response to this prompt, the agent selected one of two test objects. Infants realized that the agent could be led through inference (Experiment 1) or memory (Experiment 2) to hold a false belief about which of the two test objects rattled. These results suggest that 18-month-olds can attribute false beliefs about non-obvious properties to others, and can do so in a non-search paradigm. These and additional results (Experiment 3) help address several alternative interpretations of false-belief findings with infants.

Scientists can reason about natural systems, including the mind and brain, in many ways, with each form of reasoning being associated with its own set of limitations. The limitations on human reasoning imply that the process of reasoning about theories and communicating those theories will be error prone; we must therefore be concerned about the reproducibility of theories whose very nature is shaped by constraints on human reasoning. The problem of reproducibility can be alleviated by computational modeling, which maximizes correspondence between the actual behavior of a posited system and its behavior inferred through reasoning and increases the fidelity of communication of our theories to others.

Recent investigations of early psychological understanding have revealed three key findings. First, young infants attribute goals and dispositions to any entity they perceive as an agent, whether human or nonhuman. Second, when interpreting an agent’s actions in a scene, young infants take into account the agent’s representation of the scene, even if this representation is less complete than their own. Third, at least by the second year of life, infants recognize that agents can hold false beliefs about a scene. Together, these findings support a system-based, mentalistic account of early psychological reasoning.

The behavioral strategy literature investigates how decision makers might use Small World Representations (SWRs) to guide their actions in situations of extreme uncertainty, but says little about how such representations should be updated during the implementation phase. In this paper, we provide a framework to capture the relationship between SWRs, unknowns and Black Swans, and, drawing on the psychology of reasoning literature, explore different heuristic methods of inquiry that decision makers might use to update their SWRs. We compare the performance of two such methods⎯disconfirmation and counterfactual reasoning⎯in highly uncertain situations characterized by ambiguous and non-definite information. We find that counterfactual reasoning is superior to disconfirmation with respect to (1) counteracting the confirmation bias, (2) promoting the exploration of the scenario space, and (3) favoring the adoption of actions able to mitigate or exploit the consequences of Black Swans.

Clinical reasoning in occupational therapy has been described using a variety of images. The present paper aims to give an overview of three major images that have been proposed in the occupational therapy literature since 1982. These are reasoning as information processing, thinking in stories or narrative reasoning, and reasoning as an interpersonal process. These three images are compared with the concept of conditional reasoning.

What accounts for how we know that certain rules of reasoning, such as reasoning by Modus Ponens, are valid? If our knowledge of validity must be based on some reasoning, then we seem to be committed to the legitimacy of rule-circular arguments for validity. This paper raises a new difficulty for the rule-circular account of our knowledge of validity. The source of the problem is that, contrary to traditional wisdom, a universal generalization cannot be inferred just on the basis of reasoning about an arbitrary object. I argue in favor of a more sophisticated constraint on reasoning by universal generalization, one which undermines a rule-circular account of our knowledge of validity.

International audience; Deductive reasoning is traditionally viewed as a unitary process involving either rule-based or visuo-spatial mechanisms. However, there is a disagreement in the neuroimaging literature on whether the data support one alternative over the other. Here we test the hypothesis that discrepancies in the literature result from the reasoning materials themselves. Using functional magnetic resonance imaging, we measure brain activity of participants while they integrate the premises of conditional arguments (primarily Modus Tollens: If P then Q; not-Q) and Relational Syllogisms (i.e., linear arguments of the sort P is to the left of Q; Q is to the left of R). We find that reasoning with Modus Tollens activates the left inferior frontal gyrus to a greater extent than the Relational Syllogisms. In contrast, the Relational Syllogisms engage the right temporo-parieto-occipital junction more than conditional arguments. This suggests that conditional reasoning relies more on so-called syntactic processes than relational reasoning, while relational reasoning may rely on visuo-spatial processes and mental imagery more than conditional reasoning. This investigative approach, together with its results, clarifies some apparently inconsistent findings in this literature by showing that the nature of the logical argument, whether it is relational or conditional, determines which neural system is engaged.

The complexity of categorical syllogisms was assessed using the relational complexity metric, which is based on the number of entities that are related in a single cognitive representation. This was compared with number of mental models in an experiment in which adult participants solved all 64 syllogisms. Both metrics accounted for similarly large proportions of the variance, showing that complexity depends on the number of categories that are related in a representation of the combined premises, whether represented in multiple mental models, or by a single model. This obviates the difficulty with mental models theory due to equivocal evidence for construction of more than one mental model. The “no valid conclusion” response was used for complex syllogisms that had valid conclusions. The results are interpreted as showing that the relational complexity metric can be applied to syllogistic reasoning, and can be integrated with mental models theory, which together account for a wide range of cognitive perf...

Despite the popularity of the Wason selection task in the psychology of reasoning, doubt remains as to whether card choices actually reflect a process of reasoning. One view is that while participants reason about the cards and their hidden sides—as indicated by protocol analysis—this reasoning merely confabulates explanations for cards that were preconsciously cued. This hypothesis has apparently been supported by studies that show that participants predominantly inspect cards which they end up selecting. In this paper, we reanalyse the data of one such study, which used eye-movement tracking to record card inspection times (Ball, Lucas, Miles, & Gale, 2003). We show that while cards favoured by matching bias are inspected for roughly equal lengths of times, their selection rates are strongly affected by their logical status. These findings strongly support a two-stage account in which attention is necessary but not sufficient for card selections. Hence, reasoning does indeed affect participants’ choices on this task.

People are renowned for their failure to consider alternative hypotheses. We compare neglect of alternative causes when people make predictive versus diagnostic probability judgments. One study with medical professionals reasoning about psychopathology and two with undergraduates reasoning about goals and actions or about causal transmission yielded the same results: neglect of alternative causes when reasoning from cause to effect but not when reasoning from effect to cause. The findings suggest that framing a problem as a diagnostic-likelihood judgment can reduce bias.

Infants are sensitive to biological motion, but do they recognize it as animate? As a first step towards answering this question, two experiments investigated whether 6-month-olds selectively attribute goals to shapes moving like animals. We habituated infants to a square moving towards one of two targets. When target locations were switched, infants reacted more to movement towards a new goal than a new location - but only if the square moved non-rigidly and rhythmically, in a schematic version of bio-mechanical movement older observers describe as animal-like (Michotte, 1963). Goal attribution was specific to schematic animal motion: It did not occur if the square moved rigidly with the same rhythm as the animate stimulus, or if the square had the same amount of non-rigid deformation, but in an inanimate configuration. The data would seem to show that perception of schematic animal motion is linked to a system for psychological reasoning from infancy. This in turn suggests that 6-month-olds may already interpret biological motion as animate.

In the fifth century c.e. , Diṇnāga introduced a distinction between inferencefor-oneself (svarthānumāna) and inference-for-others (parārthānumāna) , which was adopted by all later pramāṇa theorists. A reevaluation of this well-known distinction has led us to some philosophically significant theses, which we propose to discuss here. Many scholars have already pointed out that (a) the aim of the Buddhists in developing a theory of inference was different from that of a formal logician; (b) svarthānumāna falls in the domain of psychology of reasoning, while parārthānumāna falls in the domain of logic proper; and (c) parārthānumāna should be considered a model-theoretic as opposed to a prooftheoretic enterprise. In consonance with these views, it is aimed to show that (1) Diṇnāga's account of good inferential process leading to sound inference as laid down in the Hetucakaraḍamaru is very similar to the Mental Model Theory proposed by P. N. Johnson-Laird and others, and (2) although Jonardon Ganeri's reinterpretation of the early Nyāya inference as a type of case-based reasoning may be extended to the Buddhist parārthānumāna , the most plausible reinterpretation of svārthānumāna can be given in terms of mental models.

Twelve-month-olds realize that when an agent cannot see an object, her incomplete perceptions still guide her goal-directed actions. What would happen if the agent had incomplete perceptions because she could see only one part of the object, for example one side of a screen? In the present research, 16-month-olds were first shown an agent who always pointed to a red object, as opposed to a black or a yellow object, suggesting that she preferred red over the other colours. Next, two screens were introduced while the agent was absent. The screens were (1) red or green on both sides; (2) red on the front (infants' side) but green on the back (the agent's side) or vice versa; or (3) only coloured red or green on the front. During test, the agent, who could see only the back of the screens, pointed to one of the two screens. The results revealed that while infants expected the agent to continue acting on her colour preference and point to the red rather than the green screen during test, they did so in accord with the agent's perception of the screens, rather than their own perceptions: they expected the agent to point to the red screen in (1), but to the green-front screen in (2), and they had no prediction of which screen the agent should point to in (3). The implications of the present findings for early psychological reasoning research are discussed.

Argumentation in artificial intelligence, often called computational dialectics, is rooted in Aristotle's idea of evaluating argumentation in a dialogue model. In contrast, Chinese traditional philosophy regards dialectics as a style of reasoning that focuses on contradictions and how to resolve them, transcend them or find the truth in both. A compromise is considered one way to resolve conflicts dialectically. In this paper, we formalize reasoning intended to derive a compromise. Both the reasoning and the compromise are defined on abstract lattices procedurally and declaratively, respectively. We prove that the reasoning is sound and complete with respect to the compromise. Then we define the concrete and sound algorithm for the reasoning on the lattice characterized by definite clausal language and generalized subsumption. Under some conditions, the reasoning offers a unified way to reason rationally whether a set of the premises is consistent or not. Such reasoning is outside the scope of logics that have the principle of explosion. Further, the compromise has a unique logical setting compared with other types of reasoning such as deduction, induction, and abduction. We incorporate the reasoning into arguments, and illustrate that the use of arguments with compromise contributes to realizing a compromise-based conflict resolution in argumentation.

This article traces the philosophical and psychological connections between causation and the conditional, if...then, across the two main paradigms used in conditional reasoning, the selection task and the conditional inference paradigm. It is argued that hypothesis testing in the selection task reflects the philosophical problems identified by Quine and Goodman for the material conditional interpretation of causal laws. Alternative formal theories to the material conditional only became available with the advent of possible worlds semantics (Lewis, 1973; Stalnaker, 1968). The relationship proposed by this semantics between counterfactual and indicative conditionals is outlined and it is concluded that moving away from the abstractions of possible worlds proposes a central role for prior knowledge in conditional inference. This conclusion is consistent with probabilistic approaches to conditional inference which provide measures of the strength of a dependency between the antecedent and the consequent of a conditional similar to those proposed in causal learning. Findings in conditional inference suggest that people are influenced not only by the strength of a dependency but also by the existence of the structural relationship, the broader causal framework in which a dependency is embedded, and the inhibitory and excitatory processes like those required to implement Causal Bayes nets or neural networks. That these findings may have a plausible explanation using the tools of current theories in causal learning suggests a potentially fruitful convergence of research in these two areas.

Over the last 15 years or so, the psychology of reasoning has been in transition-from an emphasis on how far people are aware of, and can reason about, deductive relations between beliefs, to an emphasis on how far people are aware of, and can reason about, probabilistic relations between degrees of belief. One strand of this work is described in our book Bayesian Rationality (Oaksford & Chater, 2007); in his insightful and valuable review David Over (2009) has woven this strand into a broader intellectual context, and raised a number of important specific issues that arise in our approach. Over raises two broad classes of issue-concerning the relationship between logic and probability, and treatment of non-monotonic inference-to which we respond in turn. In both cases we believe Over's observations provide both an important stimulus for us to clarify and develop our ideas, and, more broadly, identify areas of key important for the future theoretical developments in the psychology of reasoning.

心理学研究感性认识形式，逻辑学研究理性认识形式。二者密切相关但却长期 分离。认知科学的建立和发展，为心理学和逻辑学的交叉融合提供了科学依据和 学科框架。在认知科学的框架下，逻辑学发生了本质的变化，产生了认知逻辑新的 研究框架。在这个框架下，心理学与逻辑学交叉融合，产生了心理逻辑这一新兴学 科。它认为逻辑推理受心理因素影响，是由人参与的、涉身的经验科学。认知逻辑 开启了当代逻辑学发展的新时代，走上了作为多学科共同工具的广阔发展道路。认 知科学的发展将带来一个学科综合交叉、问题引领科学研究、科学研究引领学科建 设、人才全面发展的新时代。 关健词: 认知科学 心理学 逻辑学 逻辑心理学 心理逻辑 Psychology that is experiential forms of cognition (lower‐order cognition), and logic that is rational forms of cognition (higher‐order cognition) have long been separated although they are closely related in the original. The establishment and development of cognitive science provides a scientific basis and an academic framework for their integration. Against the background of cognitive science, logic has undergone fundamental changes, resulting in the new research framework of so‐called “cognitive logic.” Within this framework, the integration of psychology and logic has given birth to the new discipline of mental logic, which holds that logical reasoning is affected by psychological factors and is an embodied...

En el presente trabajo se analizan algunos factores o aspectos que pueden influir en la evaluación de los enunciados condicionales. El objetivo final es proporcionar un marco metodológico de evaluación de este tipo de enunciados como verdaderos o falsos sin tener en cuenta exclusivamente los valores de verdad del antecedente y del consecuente tal y como tradicionalmente ha propuesto la Lógica Formal. The aim of this work is to analyze some aspects that can have an influence on our evaluation of conditional statements. The final purpose is to provide a methodological frame of evaluation of this kind of statements without taking into account the truth values of antecedent and consequent as Formal Logic has been usually assumed.

Human cognition requires coping with a complex and uncertain world. This suggests that dealing with uncertainty may be the central challenge for human reasoning. InBayesian Rationalitywe argue that probability theory, the calculus of uncertainty, is the right framework in which to understand everyday reasoning. We also argue that probability theory explains behavior, even on experimental tasks that have been designed to probe people's logical reasoning abilities. Most commentators agree on the centrality of uncertainty; some suggest that there is a residual role for logic in understanding reasoning; and others put forward alternative formalisms for uncertain reasoning, or raise specific technical, methodological, or empirical challenges. In responding to these points, we aim to clarify the scope and limits of probability and logic in cognitive science; explore the meaning of the “rational” explanation of cognition; and re-evaluate the empirical case for Bayesian rationality.

According to Aristotle, humans are the rational animal. The borderline between rationality and irrationality is fundamental to many aspects of human life including the law, mental health, and language interpretation. But what is it to be rational? One answer, deeply embedded in the Western intellectual tradition since ancient Greece, is that rationality concerns reasoning according to the rules of logic – the formal theory that specifies the inferential connections that hold with certainty between propositions. Piaget viewed logical reasoning as defining the end-point of cognitive development; and contemporary psychology of reasoning has focussed on comparing human reasoning against logical standards.Bayesian Rationalityargues that rationality is defined instead by the ability to reason aboutuncertainty. Although people are typically poor at numerical reasoning about probability, human thought is sensitive to subtle patterns of qualitative Bayesian, probabilistic reasoning. In Chapters 1–4 ofBayesian Rationality(Oaksford & Chater 2007), the case is made that cognition in general, and human everyday reasoning in particular, is best viewed as solving probabilistic, rather than logical, inference problems. In Chapters 5–7 the psychology of “deductive” reasoning is tackled head-on: It is argued that purportedly “logical” reasoning problems, revealing apparently irrational behaviour, are better understood from a probabilistic point of view. Data from conditional reasoning, Wason's selection task, and syllogistic inference are captured by recasting these problems probabilistically. The probabilistic approach makes a variety of novel predictions which have been experimentally confirmed. The book considers the implications of this work, and the wider “probabilistic turn” in cognitive science and artificial intelligence, for understanding human rationality.

Comparing the three-form reasoning of new Hetu-vidya with Western logic, scholars have put forward four perspectives. Combining their strengths and shortcomings, and the examples of Hetu-vidya reasoning, we can conclude that the three-form reasoning should have four forms: (1) the affirmative expression of formal implication; (2) the modus ponens of hypothetical reasoning concerning sufficient conditions after universal instantiation; (3) the negative expression of a formal implication; and (4) the modus tollens of hypothetical reasoning concerning sufficient conditions after universal instantiation.

Do 18-month-olds understand that an agent's false belief can be corrected by an appropriate, though not an inappropriate, communication? In Experiment 1, infants watched a series of events involving two agents, a ball, and two containers: a box and a cup. To start, agent1 played with the ball and then hid it in the box, while agent2 looked on. Next, in agent1's absence, agent2 moved the ball from the box to the cup. When agent1 returned, agent2 told her "The ball is in the cup!" (informative-intervention condition) or "I like the cup!" (uninformative-intervention condition). During test, agent1 reached for either the box (box event) or the cup (cup event). In the informative-intervention condition, infants who saw the box event looked reliably longer than those who saw the cup event; in the uninformative-intervention condition, the reverse pattern was found. These results suggest that infants expected agent1's false belief about the ball's location to be corrected when she was told "The ball is in the cup!", but not "I like the cup!". In Experiment 2, agent2 simply pointed to the ball's new location, and infants again expected agent1's false belief to be corrected. These and control results provide additional evidence that infants in the second year of life can attribute false beliefs to agents. In addition, the results suggest that by 18 months of age infants expect agents' false beliefs to be corrected by relevant communications involving words or gestures.

In this paper practical reasoning is understood in the Aristotelian sense as reasoning leading to action or to an intention to do something. Georg Henrik von Wright and a number of other philosophers have tried to assimilate certain forms of such reasoning to deductive reasoning. Many examples of practical reasoning, including some examples given by Aristotle, do not fit a deductive or quasi-deductive model. It is argued that instances of good practical reasoning often resemble abductive rather than deductive or inductive reasoning, and that the principles governing abduction, including the Principle of Economy, are applicable to practical reasoning.