How To Build A Brain

Author: Chris Eliasmith
Publisher: Oxford University Press
ISBN: 0199794545
Size: 56.61 MB
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Chris Eliasmith presents a new approach to understanding the neural implementation of cognition in a way that is centrally driven by biological considerations. According to the Semantic Pointer Hypothesis, higher-level cognitive functions in biological systems are made possible by semantic pointers.

How To Build A Brain

Author: Chris Eliasmith
Publisher: Oxford University Press
ISBN: 0199794693
Size: 34.41 MB
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How to Build a Brain provides a detailed exploration of a new cognitive architecture - the Semantic Pointer Architecture - that takes biological detail seriously, while addressing cognitive phenomena. Topics ranging from semantics and syntax, to neural coding and spike-timing-dependent plasticity are integrated to develop the world's largest functional brain model.

How Can The Human Mind Occur In The Physical Universe

Author: John R. Anderson
Publisher: Oxford University Press
ISBN: 0199741263
Size: 51.38 MB
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"The question for me is how can the human mind occur in the physical universe. We now know that the world is governed by physics. We now understand the way biology nestles comfortably within that. The issue is how will the mind do that as well."--Allen Newell, December 4, 1991, Carnegie Mellon University The argument John Anderson gives in this book was inspired by the passage above, from the last lecture by one of the pioneers of cognitive science. Newell describes what, for him, is the pivotal question of scientific inquiry, and Anderson gives an answer that is emerging from the study of brain and behavior. Humans share the same basic cognitive architecture with all primates, but they have evolved abilities to exercise abstract control over cognition and process more complex relational patterns. The human cognitive architecture consists of a set of largely independent modules associated with different brain regions. In this book, Anderson discusses in detail how these various modules can combine to produce behaviors as varied as driving a car and solving an algebraic equation, but focuses principally on two of the modules: the declarative and procedural. The declarative module involves a memory system that, moment by moment, attempts to give each person the most appropriate possible window into his or her past. The procedural module involves a central system that strives to develop a set of productions that will enable the most adaptive response from any state of the modules. Newell argued that the answer to his question must take the form of a cognitive architecture, and Anderson organizes his answer around the ACT-R architecture, but broadens it by bringing in research from all areas of cognitive science, including how recent work in brain imaging maps onto the cognitive architecture.

Neural Engineering

Author: Chris Eliasmith
Publisher: MIT Press
ISBN: 9780262550604
Size: 26.63 MB
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A synthesis of current approaches to adapting engineering tools to the study of neurobiological systems.

Neural Information Processing

Author: Akira Hirose
Publisher: Springer
ISBN: 3319466879
Size: 63.45 MB
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The four volume set LNCS 9947, LNCS 9948, LNCS 9949, and LNCS 9950 constitutes the proceedings of the 23rd International Conference on Neural Information Processing, ICONIP 2016, held in Kyoto, Japan, in October 2016. The 296 full papers presented were carefully reviewed and selected from 431 submissions. The 4 volumes are organized in topical sections on deep and reinforcement learning; big data analysis; neural data analysis; robotics and control; bio-inspired/energy efficient information processing; whole brain architecture; neurodynamics; bioinformatics; biomedical engineering; data mining and cybersecurity workshop; machine learning; neuromorphic hardware; sensory perception; pattern recognition; social networks; brain-machine interface; computer vision; time series analysis; data-driven approach for extracting latent features; topological and graph based clustering methods; computational intelligence; data mining; deep neural networks; computational and cognitive neurosciences; theory and algorithms.

Exploring Robotic Minds

Author: Jun Tani
Publisher: Oxford University Press
ISBN: 0190281073
Size: 14.69 MB
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In Exploring Robotic Minds: Actions, Symbols, and Consciousness as Self-Organizing Dynamic Phenomena, Jun Tani sets out to answer an essential and tantalizing question: How do our minds work? By providing an overview of his "synthetic neurorobotics" project, Tani reveals how symbols and concepts that represent the world can emerge in a neurodynamic structure--iterative interactions between the top-down subjective view, which proactively acts on the world, and the bottom-up recognition of the resultant perceptual reality. He argues that nontrivial problems of consciousness and free will could be addressed through structural understanding of such iterative, conflicting interactions between the top-down and the bottom-up pathways. A wide range of readers will enjoy this wonderful journey of the mind and will follow the author on interdisciplinary discussions that span neuroscience, dynamical systems theories, robotics, and phenomenology. The book also includes many figures, as well as a link to videos of Tani's exciting robotic experiments.

Minding Norms

Author: Rosaria Conte
Publisher: Oxford University Press
ISBN: 0199812675
Size: 28.78 MB
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This volume presents an unprecedented attempt to illustrate via agent based simulation the emergence of norms meant as prescribed conducts applied by the majority. The simulated scenarios are populated with cognitive agents generating norms by detecting and deciding to respect them.

Social Emotions In Nature And Artifact

Author: Jonathan Gratch
Publisher: Oxford University Press
ISBN: 0199314497
Size: 64.60 MB
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Recent years have seen the rise of a remarkable partnership between the social and computational sciences on the phenomena of emotions. Rallying around the term Affective Computing, this research can be seen as revival of the cognitive science revolution, albeit garbed in the cloak of affect, rather than cognition. Traditional cognitive science research, to the extent it considered emotion at all, cases it as at best a heuristic but more commonly a harmful bias to cognition. More recent scholarship in the social sciences has upended this view. Increasingly, emotions are viewed as a form of information processing that serves a functional role in human cognition and social interactions. Emotions shape social motives and communicate important information to social partners. When communicating face-to-face, people can rapidly detect nonverbal affective cues, make inferences about the other party's mental state, and respond in ways that co-construct an emotional trajectory between participants. Recent advances in biometrics and artificial intelligence are allowing computer systems to engage in this nonverbal dance, on the one hand opening a wealth of possibilities for human-machine systems, and on the other, creating powerful new tools for behavioral science research. Social Emotions in Nature and Artifact reports on the state-of-the-art in both social science theory and computational methods, and illustrates how these two fields, together, can both facilitate practical computer/robotic applications and illuminate human social processes.

The Soar Cognitive Architecture

Author: John E. Laird
Publisher: MIT Press
ISBN: 0262300354
Size: 29.53 MB
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In development for thirty years, Soar is a general cognitive architecture that integrates knowledge-intensive reasoning, reactive execution, hierarchical reasoning, planning, and learning from experience, with the goal of creating a general computational system that has the same cognitive abilities as humans. In contrast, most AI systems are designed to solve only one type of problem, such as playing chess, searching the Internet, or scheduling aircraft departures. Soar is both a software system for agent development and a theory of what computational structures are necessary to support human-level agents. Over the years, both software system and theory have evolved. This book offers the definitive presentation of Soar from theoretical and practical perspectives, providing comprehensive descriptions of fundamental aspects and new components. The current version of Soar features major extensions, adding reinforcement learning, semantic memory, episodic memory, mental imagery, and an appraisal-based model of emotion. This book describes details of Soar's component memories and processes and offers demonstrations of individual components, components working in combination, and real-world applications. Beyond these functional considerations, the book also proposes requirements for general cognitive architectures and explicitly evaluates how well Soar meets those requirements.

Fundamentals Of Neural Network Modeling

Author: Randolph W. Parks
Publisher: MIT Press
ISBN: 9780262161756
Size: 16.50 MB
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Provides an introduction to the neural network modeling of complex cognitive and neuropsychological processes.