Books in Cognitive science

Cognitive Big Data Intelligence with a Metaheuristic Approach

1st Edition
November 9, 2021
Sushruta Mishra + 4 more
English
Paperback
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eBook
9 7 8 0 3 2 3 8 5 1 1 8 3

Cognitive Big Data Intelligence with a Metaheuristic Approach presents an exact and compact organization of content relating to the latest metaheuristics methodologies based on new challenging big data application domains and cognitive computing. The combined model of cognitive big data intelligence with metaheuristics methods can be used to analyze emerging patterns, spot business opportunities, and take care of critical process-centric issues in real-time. Various real-time case studies and implemented works are discussed in this book for better understanding and additional clarity. This book presents an essential platform for the use of cognitive technology in the field of Data Science. It covers metaheuristic methodologies that can be successful in a wide variety of problem settings in big data frameworks.

Intelligent Systems and Learning Data Analytics in Online Education

1st Edition
June 15, 2021
Santi Caballé + 4 more
English
Paperback
9 7 8 0 1 2 8 2 3 4 1 0 5
eBook
9 7 8 0 1 2 8 2 3 1 2 7 2

Intelligent Systems and Learning Data Analytics in Online Education provides novel artificial intelligence (AI) and analytics-based methods to improve online teaching and learning. This book addresses key problems such as attrition and lack of engagement in MOOCs and online learning in general. This book explores the state of the art of artificial intelligence, software tools and innovative learning strategies to provide better understanding and solutions to the various challenges of current e-learning in general and MOOC education. In particular, Intelligent Systems and Learning Data Analytics in Online Education shares stimulating theoretical and practical research from leading international experts. This publication provides useful references for educational institutions, industry, academic researchers, professionals, developers, and practitioners to evaluate and apply.

Human-Machine Shared Contexts

1st Edition
June 9, 2020
William Lawless + 2 more
English
Paperback
9 7 8 0 1 2 8 2 0 5 4 3 3
eBook
9 7 8 0 1 2 8 2 2 3 7 9 6

Human-Machine Shared Contexts considers the foundations, metrics, and applications of human-machine systems. Editors and authors debate whether machines, humans, and systems should speak only to each other, only to humans, or to both and how. The book establishes the meaning and operation of “shared contexts” between humans and machines; it also explores how human-machine systems affect targeted audiences (researchers, machines, robots, users) and society, as well as future ecosystems composed of humans and machines. This book explores how user interventions may improve the context for autonomous machines operating in unfamiliar environments or when experiencing unanticipated events; how autonomous machines can be taught to explain contexts by reasoning, inferences, or causality, and decisions to humans relying on intuition; and for mutual context, how these machines may interdependently affect human awareness, teams and society, and how these "machines" may be affected in turn. In short, can context be mutually constructed and shared between machines and humans? The editors are interested in whether shared context follows when machines begin to think, or, like humans, develop subjective states that allow them to monitor and report on their interpretations of reality, forcing scientists to rethink the general model of human social behavior. If dependence on machine learning continues or grows, the public will also be interested in what happens to context shared by users, teams of humans and machines, or society when these machines malfunction. As scientists and engineers "think through this change in human terms," the ultimate goal is for AI to advance the performance of autonomous machines and teams of humans and machines for the betterment of society wherever these machines interact with humans or other machines. This book will be essential reading for professional, industrial, and military computer scientists and engineers; machine learning (ML) and artificial intelligence (AI) scientists and engineers, especially those engaged in research on autonomy, computational context, and human-machine shared contexts; advanced robotics scientists and engineers; scientists working with or interested in data issues for autonomous systems such as with the use of scarce data for training and operations with and without user interventions; social psychologists, scientists and physical research scientists pursuing models of shared context; modelers of the internet of things (IOT); systems of systems scientists and engineers and economists; scientists and engineers working with agent-based models (ABMs); policy specialists concerned with the impact of AI and ML on society and civilization; network scientists and engineers; applied mathematicians (e.g., holon theory, information theory); computational linguists; and blockchain scientists and engineers.

MATLAB for Neuroscientists

1st Edition
October 29, 2008
Pascal Wallisch + 5 more
English
eBook
9 7 8 0 0 8 0 9 2 3 2 8 4

MATLAB for Neuroscientists: An Introduction to Scientific Computing in MATLAB is the first comprehensive teaching resource and textbook for the teaching of MATLAB in the Neurosciences and in Psychology. MATLAB is unique in that it can be used to learn the entire empirical and experimental process, including stimulus generation, experimental control, data collection, data analysis and modeling. Thus a wide variety of computational problems can be addressed in a single programming environment. The idea is to empower advanced undergraduates and beginning graduate students by allowing them to design and implement their own analytical tools. As students advance in their research careers, they will have achieved the fluency required to understand and adapt more specialized tools as opposed to treating them as "black boxes". Virtually all computational approaches in the book are covered by using genuine experimental data that are either collected as part of the lab project or were collected in the labs of the authors, providing the casual student with the look and feel of real data. In some cases, published data from classical papers are used to illustrate important concepts, giving students a computational understanding of critically important research.

Handbook of Cognitive Science

1st Edition
August 15, 2008
Paco Calvo + 1 more
English
Hardback
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eBook
9 7 8 0 0 8 0 9 1 4 8 7 9

The Handbook of Cognitive Science provides an overview of recent developments in cognition research, relying upon non-classical approaches. Cognition is explained as the continuous interplay between brain, body, and environment, without relying on classical notions of computations and representation to explain cognition. The handbook serves as a valuable companion for readers interested in foundational aspects of cognitive science, and neuroscience and the philosophy of mind. The handbook begins with an introduction to embodied cognitive science, and then breaks up the chapters into separate sections on conceptual issues, formal approaches, embodiment in perception and action, embodiment from an artificial perspective, embodied meaning, and emotion and consciousness. Contributors to the book represent research overviews from around the globe including the US, UK, Spain, Germany, Switzerland, France, Sweden, and the Netherlands.

Philosophy of Psychology and Cognitive Science

1st Edition
October 23, 2006
Dov M. Gabbay + 2 more
English
eBook
9 7 8 0 0 8 0 4 6 6 6 2 0

Psychology is the study of thinking, and cognitive science is the interdisciplinary investigation of mind and intelligence that also includes philosophy, artificial intelligence, neuroscience, linguistics, and anthropology. In these investigations, many philosophical issues arise concerning methods and central concepts. The Handbook of Philosophy of Psychology and Cognitive Science contains 16 essays by leading philosophers of science that illuminate the nature of the theories and explanations used in the investigation of minds. Topics discussed include representation, mechanisms, reduction, perception, consciousness, language, emotions, neuroscience, and evolutionary psychology.

Neuromimetic Semantics

1st Edition
May 6, 2004
Harry Howard
English
eBook
9 7 8 0 0 8 0 5 3 7 4 4 3

This book attempts to marry truth-conditional semantics with cognitive linguistics in the church of computational neuroscience. To this end, it examines the truth-conditional meanings of coordinators, quantifiers, and collective predicates as neurophysiological phenomena that are amenable to a neurocomputational analysis. Drawing inspiration from work on visual processing, and especially the simple/complex cell distinction in early vision (V1), we claim that a similar two-layer architecture is sufficient to learn the truth-conditional meanings of the logical coordinators and logical quantifiers. As a prerequisite, much discussion is given over to what a neurologically plausible representation of the meanings of these items would look like. We eventually settle on a representation in terms of correlation, so that, for instance, the semantic input to the universal operators (e.g. and, all)is represented as maximally correlated, while the semantic input to the universal negative operators (e.g. nor, no)is represented as maximally anticorrelated. On the basis this representation, the hypothesis can be offered that the function of the logical operators is to extract an invariant feature from natural situations, that of degree of correlation between parts of the situation. This result sets up an elegant formal analogy to recent models of visual processing, which argue that the function of early vision is to reduce the redundancy inherent in natural images. Computational simulations are designed in which the logical operators are learned by associating their phonological form with some degree of correlation in the inputs, so that the overall function of the system is as a simple kind of pattern recognition. Several learning rules are assayed, especially those of the Hebbian sort, which are the ones with the most neurological support. Learning vector quantization (LVQ) is shown to be a perspicuous and efficient means of learning the patterns that are of interest. We draw a formal parallelism between the initial, competitive layer of LVQ and the simple cell layer in V1, and between the final, linear layer of LVQ and the complex cell layer in V1, in that the initial layers are both selective, while the final layers both generalize. It is also shown how the representations argued for can be used to draw the traditionally-recogn... inferences arising from coordination and quantification, and why the inference of subalternacy breaks down for collective predicates. Finally, the analogies between early vision and the logical operators allow us to advance the claim of cognitive linguistics that language is not processed by proprietary algorithms, but rather by algorithms that are general to the entire brain. Thus in the debate between objectivist and experiential metaphysics, this book falls squarely into the camp of the latter. Yet it does so by means of a rigorous formal, mathematical, and neurological exposition – in contradiction of the experiential claim that formal analysis has no place in the understanding of cognition. To make our own counter-claim as explicit as possible, we present a sketch of the LVQ structure in terms of mereotopology, in which the initial layer of the network performs topological operations, while the final layer performs mereological operations. The book is meant to be self-contained, in the sense that it does not assume any prior knowledge of any of the many areas that are touched upon. It therefore contains mini-summaries of biological visual processing, especially the retinocortical and ventral /what?/ parvocellular pathways; computational models of neural signaling, and in particular the reduction of the Hodgkin-Huxley equations to the connectionist and integrate-and-fire neurons; Hebbian learning rules and the elaboration of learning vector quantization; the linguistic pathway in the left hemisphere; memory and the hippocampus; truth-conditional vs. image-schematic semantics; objectivist vs. experiential metaphysics; and mereotopology. All of the simulations are implemented in MATLAB, and the code is available from the book’s website.

Agenda Relevance: A Study in Formal Pragmatics

1st Edition
Volume 1
May 29, 2003
Dov M. Gabbay + 1 more
English
eBook
9 7 8 0 0 8 0 5 2 6 8 7 4

Agenda Relevance is the first volume in the authors' omnibus investigation ofthe logic of practical reasoning, under the collective title, A Practical Logicof Cognitive Systems. In this highly original approach, practical reasoning isidentified as reasoning performed with comparatively few cognitive assets,including resources such as information, time and computational capacity. Unlikewhat is proposed in optimization models of human cognition, a practical reasonerlacks perfect information, boundless time and unconstrained access tocomputational complexity. The practical reasoner is therefore obliged to be acognitive economizer and to achieve his cognitive ends with considerableefficien... Accordingly, the practical reasoner avails himself of variousscarce-resour... compensation strategies. He also possesses neurocognitivetraits that abet him in his reasoning tasks. Prominent among these is thepractical agent's striking (though not perfect) adeptness at evading irrelevantinformatio... and staying on task. On the approach taken here, irrelevancies areimpediments to the attainment of cognitive ends. Thus, in its most basic sense,relevant information is cognitively helpful information. Information can then besaid to be relevant for a practical reasoner to the extent that it advances orcloses some cognitive agenda of his. The book explores this idea with aconceptual detail and nuance not seen the standard semantic, probabilistic andpragmatic approaches to relevance; but wherever possible, the authors seek tointegrate alternative conceptions rather than reject them outright. A furtherattraction of the agenda-relevance approach is the extent to which its principalconceptual findings lend themselves to technically sophisticated re-expressionin formal models that marshal the resources of time and action logics andlabel led deductive systems. Agenda Relevance is necessary reading for researchers in logic, beliefdynamics, computer science, AI, psychology and neuroscience, linguistics,argument... theory, and legal reasoning and forensic science, and will repaystudy by graduate students and senior undergraduates in these same fields.Key features:• relevance• action and agendas• practical reasoning• belief dynamics• non-classical logics• labelled deductive systems

Handbook of the Logic of Argument and Inference

1st Edition
Volume 1
September 11, 2002
R.H. Johnson + 3 more
English
eBook
9 7 8 0 0 8 0 5 3 2 9 1 2

The Handbook of the Logic of Argument and Inference is an authoritative reference work in a single volume, designed for the attention of senior undergraduates, graduate students and researchers in all the leading research areas concerned with the logic of practical argument and inference. After an introductory chapter, the role of standard logics is surveyed in two chapters. These chapters can serve as a mini-course for interested readers, in deductive and inductive logic, or as a refresher. Then follow two chapters of criticism; one the internal critique and the other the empirical critique. The first deals with objections to standard logics (as theories of argument and inference) arising from the research programme in philosophical logic. The second canvasses criticisms arising from work in cognitive and experimental psychology. The next five chapters deal with developments in dialogue logic, interrogative logic, informal logic, probability logic and artificial intelligence. The last chapter surveys formal approaches to practical reasoning and anticipates possible future developments. Taken as a whole the Handbook is a single-volume indication of the present state of the logic of argument and inference at its conceptual and theoretical best. Future editions will periodically incorporate significant new developments.

Animal Cognition and Behavior

1st Edition
Volume 13
April 1, 2000
R.L. Mellgren
English
eBook
9 7 8 0 0 8 0 8 6 6 6 7 3

Contributed chapters by psychologists and behavioral biologists provide a broad coverage of animal behavior, and governing brain processes. Topics covered include: foraging behavior and strategies, economics and psychology, memory of events and space, time perception, expectancies, food preferences and diet selection, behavior variability and the concept of mind.The volume is designed to satisfy an intderdisciplinary audience, embracing the behavioristic tradition, biological and physiological approaches, and evolutionary theory as philosophical underpinnings to the chapters. Also achieved in this work is a good balance between empirical results and theory.

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