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This chapter contains sections titled: Background The Turing Test Simulation of Human Expertise Neural Networks Definition of Intelligence Intelligence, the Scientific Method, and Evolution Evolving Artificial Intelligence References Chapter 1 Exercises

This review discusses the role of psychology in the development in the sector of artificial intelligence. Cognitive science bestows the scientific basis for advancement in the realm of artificial intelligence. Gleaning a high-tech machine that can think, learn, reason, experience, and can function autarchic bereft of supervision is one of the pivotal grails in all of computer science. Studies posit that higher education in psychology can smooth the path for reasoning about general issues. With a prodigiously autarchic, learning, reasoning, the artificially intelligent system comes with a need to possess hardware and software that transcribes processes and subsystems that subsist within a human brain including intuitive and emotional concepts. The idea of interweaving these two immense realms: the complexities of psychology and vitality of artificial intelligence has gained escalation in recent times. This review focuses on how computer implementation and psychological tools bring enhancement in the field of artificial intelligence.

Today, video games are a multi-billion-dollar industry, continuously evolving through the incorporation of new technologies and innovative design. However, current video game software content creation requires extensive and often-times ambiguous planning phases for developing aesthetics, online capabilities, and gameplay mechanics. Design elements can vary significantly relative to the expertise of artists, designers, budget, and overall game engine/software features and capabilities. Game development processes are often extensively long coding sessions, usually involving a highly iterative creative process, where user requirements are rarely provided. Therefore, we propose significantly simplifying game design and development with novel Artificial Cognition Architecture real-time scalability and dynamic emotion core. Rather than utilizing more static emotion state weighting emotion engines (e.g. ExAI), we leverage significant ACA research in successful implementation of analog neural learning bots with Maslowan objective function algorithms. We also leverage AI- based Artificial Psychology software which utilizes ACA’s fine grained self-evolving emotion modeling in humanistic avatar patients for Psychologist training. An ACA common cognitive core provides the gaming industry with wider applications across video game genres. A modular, scalable, and cognitive emotion game architecture implements Non-Playable Character (NPC) learning and self-evolution. ACA models NPC’s with fine grained emotions, providing interactive dynamic personality traits for a more realistic game environment and enables NPC self-evolution under the influence of both other NPC’s and players. Furthermore, we explore current video game design engine architecture (e.g. Unity, Unreal Engine) and propose an ACA integration approach. We apply artificial cognition and emotion intelligence modeling to engender video games with more distinct, realistic consumer gaming experiences, while simultaneously minimizing software gaming development efforts and costs.

Due to information technology development and its industrial adaptation, the dilemmas so far specific to philosophical speculations and science-fiction literature and films have become the real problems of the contemporary world. On one hand, these issues are related to an unprecedented scale on which computational algorithms are currently used as well as a level of complexity of mutual connections; on the other hand, these are linked to their autonomous behavior. States, industry, and users themselves demand formulation of understandable ethical categories and determination of transparency standards and legal norms for these algorithms’ functioning in the near future.

This paper is mainly on the emergent intelligence associated with artificial life and its principals. In order to analyze the model adaptive or intelligent behaviors, economic theory to artificial life can be applied. The principles whereby an animated competent for its resources, and to survey the intelligent behavior are the main concern of this research. The level of decision making, cost function and utility behavior (the macroeconomic level), physiological and goal oriented behavior are the qualities of this literature survey which are investigated. The behavior of the agent can be analyzed using many different metrics; for example, competition, metabolic activity and economic interaction with respect to macro-microeconomics and environment.

Working professionals life in metropolitan city seems to be worst with full of stress and anxiety. With hectic schedule they don’t even have time for their family. In order to overcome stress and to even get entertained and to relax they can consider games as an important medium. To remove boredom from life and to make sure that life is interesting and exciting they should be entertained. After heavy work schedules no one will effort to go out to get relaxed. There are many ways through which people can get entertained. We are going to focus on one of the methods of entertainment that is through video games. Video games have got many pros and cons generally many people will focus on the cons like continuous playing of games will lead to health problems like problem in eye sight apart from the cons there are pros like attaining success in professional life because these games it helps in making faster decisions since next move has to be made immediately as every game has to be played within limited span of time. Video games also helps in career boost like understanding leadership qualities and performing any task by following strategies through which goals can be attained with in stipulated time. Video game AI (artificial intelligence) is inspired by the human ability to identify the correlation between the games and applying same behavior on conceptual level. Human behavior varies based on the conceptual view and actions. For any video game there should be any medium through which human being can interact like graphical user interface, scripting API and plug-in API. The programming model that is followed is based on time simulation. There are many other challenges faced in the artificial intelligence or computational intelligence techniques while creating and designing video games. Problem arises when a human plays with an entity that performs human like actions. In which decisions are not controlled by human player. In this paper we try to explore how to design conceptual AI and how to integrate conceptual AI in video games and discuss about interfaces like graphical user interface, scripting API, plug-in API and challenges faced like game artificial intelligence,non-player characters, procedural content generation,affective computing,human-like behavior.

The term "Cognitive Architectures" indicates both abstract models of cognition, in natural and artificial agents, and the software instantiations of such models which are then employed in the field ...

The history of inferences at the Yale Artificial Intelligence Project is discussed. (Author)

The origin of artificial intelligence is investigated, based on which the concepts of hybrid intelligence and parallel intelligence are presented. The paradigm shift in Intelligence indicates the ``new normal'' of cyber-social-physical systems (CPSS), in which the system behaviors are guided by Merton's Laws. Thus, the ACP-based parallel intelligence consisting of Artificial societies, Computational experiments and Parallel execution are introduced to bridge the big modeling gap in CPSS.

Gray et al. (2014) examined the productivity of expert systems/artificial intelligence research in accounting and came to the conclusion that both research on and practice use of expert systems/artificial intelligence had waned since the late 1990s. In our study, we reconsider these findings based on a broader view that is ‘artificial intelligence’ centric versus ‘expert systems’ centric. The results show that while there was a bit of a lull in the late 1990s, artificial intelligence research in accounting has continued to steadily increase over the past 30 years. Further consideration of artificial intelligence techniques as embedded modules in integrated audit support systems also suggest that use by practice continues to be robust. Based on these findings, we make a call for much more research on the usability, and use, of artificial intelligence techniques in accounting domains. Contrary to earlier perceptions, the research domain remains vibrant and holds great potential for AIS researchers to take a leadership role in advancing the field.

Artificial General Intelligence is a field of research aiming to distill the principles of intelligence that operate independently of a specific problem domain or a predefined context and utilize these principles in order to synthesize systems capable of performing any intellectual task a human being is capable of and eventually go beyond that. While "narrow" artificial intelligence which focuses on solving specific problems such as speech recognition, text comprehension, visual pattern recognition, robotic motion, etc. has shown quite a few impressive breakthroughs lately, understanding general intelligence remains elusive. In the paper we offer a novel theoretical approach to understanding general intelligence. We start with a brief introduction of the current conceptual approach. Our critique exposes a number of serious limitations that are traced back to the ontological roots of the concept of intelligence. We then propose a paradigm shift from intelligence perceived as a competence of individual agents defined in relation to an a priori given problem domain or a goal, to intelligence perceived as a formative process of self-organization by which intelligent agents are individuated. We call this process open-ended intelligence. Open-ended intelligence is developed as an abstraction of the process of cognitive development so its application can be extended to general agents and systems. We introduce and discuss three facets of the idea: the philosophical concept of individuation, sense-making and the individuation of general cognitive agents. We further show how open-ended intelligence can be framed in terms of a distributed, self-organizing network of interacting elements and how such process is scalable. The framework highlights an important relation between coordination and intelligence and a new understanding of values. We conclude with a number of questions for future research., Preprint; 35 pages, 2 figures; Keywords: intelligence, cognition, individuation, assemblage, self-organization, sense-making, coordination, enaction; en-US proofreading

The PhD thesis "On Cognitive Aspects of Human-Level Artificial Intelligence" summarises several connected lines of work from the field of human-level artificial intelligence (HLAI) research. Among others, complexity and approximation properties of the heuristic-driven theory projection analogy engine have been examined, and the framework has been applied to modelling tasks in cognitive psychology and the learning sciences. Additionally, the general importance and applicability of formal methods as potential guidance for research and development of systems in AI/HLAI has been outlined and exemplified. Finally, questions for the scientific status of AI/HLAI and for means of assessing or measuring progress in the field have been discussed.

In the last two decades, researchers have found many advantages related to Artificial Intelligence (AI) in the performance of both service and manufacturing systems. It includes alternate methods to conventional techniques and there are mechanisms of integrated systems. Currently, many researches related to artificial intelligence are under process. At present, artificial intelligence has been used to solve various problems in several fields and has become more popular around the world. This field is extremely difficult to review either chronologically or thematically. AI has a long history of growing constantly and changing tremendously. Connected with the history of computers, artificial intelligence is the main concept behind the fifth generation computers. This review paper deals with the framework of artificial intelligence and focuses on fields related to artificial intelligence. Particularly this paper describes about the recent growth in the field of artificial intelligence and its applications. Several issues of artificial intelligence are analysed. It is concluded that still many researches are yet to be conducted for further growth in the field of Artificial Intelligence (AI).

A modification of the paradigm of Artificial Intelligence (AI) is proposed in the paper. The modification is based on the assumption that there are algorithms which are inductive by construction, but can be mathematically proved. The content of traditional artificial intelligence concepts (knowledge, form of presentation, knowledge base, etc.) is determined within the proposed paradigm. The modification ensures unification of many concepts in the field of artificial intelligence.

The sociological dimension of Artificial Intelligence (AI), and automation, is placed in the path traced by the man-machine integration process, started in the eighteenth century by the Industrial Revolution that assumes its current connotation after World War II. The use of the term intelligence, which appears in the expression Artificial Intelligence, is shown to be improper and misleading, and the expression itself should be replaced, eventually, by Artificial Simulation of the Savant Syndrome. By adopting a theoretical perspective, namely Endo-Dynamo-Tensive Model [Messori 2012B], it is traced the mapping of human’s neurological (neuro-dynamics) and psychological (psycho-dynamics) dimension, and is provided the coordinates to be followed in the phenomenological qualification and definition of the psychic-mental-cognitive function intelligence. The neuro-dynamics of the Nervous System (NS), is taken into account by adopting the theoretical, interpretative and investigative perspective indicated by the particular line of research developed in the context of Quantum Field Theory (QFT) and QED (Quantum Electrodynamic Field Theory), that describes the water of which all living systems are composed, i.e. biological water, as water in a coherent oscillatory phase or state other than that of common water, named super-coherent oscillatory state. By introducing the possible functional role exerted within brain activity by glial cells, cerebrospinal fluid, intra- and extra-cellular fluid is outlined the overcoming of the classical neuroscience paradigm, based on the vision of brain activity as ruled by networks of neurons interconnected by synapses. The body-mind hard problem is taken into account and a solution is advanced. The psycho-dynamics of the humans mind territory is taken into account according to the four poles of mental functions introduced by C.G. Jung in his Psychological Types (1921), where he introduces a hierarchy of mental functions in two mental bipolar dimensions (dichotomies). These are sensing (attentiveness by means of the sense organs) coupled to intuition (awareness in unconscious way or being aware of unconscious contents) and thinking (function of intellectual cognition; the forming of logical conclusions) coupled to feeling (function of subjective estimation). At the conclusion of this work, it is provided the phenomenological definition of intelligence that does not contemplate the possibility to apply to neuroscience, and to natural and human sciences in general, the paradigm that inspires the research on AI, i.e. computational model and Information Theory.

In the spirit of the subject of the XXXIII AESLA International Conference, multimodal communication in the 21 st century, this paper offers a modest theoretical approach of the implementation of the predicative structure of the verb in Spanish to artificial intelligence by employing cognitive computing and machine learning.

The papers in this special section presents state-of-the-art research in the area of human-level artificial intelligence and robotic systems from a complex systems perspective. These papers aim to explore questions such as: What is a reasonable cognitive framework? How to build an embodied robotics system? How complex is human-level intelligence? What kinds of subsystems must be integrated to achieve human-level intelligence? To what degree does human-level intelligence rely on emergent properties? To what extent is complexity science (attractors, self-organizing criticality, network theory, and so on) useful for understanding human-level intelligence? To what extent can human-level intelligence be achieved by integrating components that have been engineered, tested, and perhaps commercially deployed for other, more specialized purposes?

Computers and Thought are the two categories that together define Artificial Intelligence as a discipline. It is generally accepted that work in Artificial Intelligence over the last thirty years has had a strong influence on aspects of computer architectures. In this paper we also make the converse claim; that the state of computer architecture has been a strong influence on our models of thought. The Von Neumann model of computation has lead Artificial Intelligence in particular directions. Intelligence in biological systems is completely different. Recent work in behavior-based Artificial Intelligence has produced new models of intelligence that are much closer in spirit to biological systems. The non-Von Neumann computational models they use share many characteristics with biological computation.