Artificial intelligence and soft computing : behavioral and cognitive modeling of the human brain /: behavioral and cognitive modeling of the human brain. (2018)

• Record Type: Book
• Further Information: Note: Amit Konar.
• Other Names: Konar, Amit; CRC Press.
• Contents: INTRODUCTION TO AI AND SOFT COMPUTING; Evolution of Computing; Defining AI; General Problem Solving Approaches in AI; The Disciplines of AI; A Brief History of AI; Characteristic Requirement for the Realization of Intelligent Systems; Programming Languages for AI; Architecture for AI Machines; Objective and Scope of the Book; Summary; THE PSYCHOLOGICAL PERSPECTIVE OF COGNITION; Introduction; The Cognitive Perspective of Pattern Recognition; Cognitive Models of Memory; Mental Imagery; Understanding a Problem; A Cybernetic View to Cognition; Scope of Realization of Cognition in AI; Summary; PRODUCTION SYSTEMS; Introduction; Production Rules; The Working Memory; The Control Unit / Interpreter; Conflict Resolution Strategies; An Alternative Approach for Conflict Resolution; An Illustrative Production System; The RETE Match Algorithm; Types of Production Systems; Forward versus Backward Production Systems; General Merits of a Production System; Knowledge Base Optimization in a Production System; Conclusions; PROBLEM SOLVING BY INTELLIGENT SEARCH; Introduction; General Problem Solving Approaches; Heuristic Search; Adversary Search; Conclusions; THE LOGIC OF PROPOSITIONS AND PREDICATES; Introduction; Formal Definitions; Tautologies in Propositional Logic; Theorem Proving by Propositional Logic; Resolution in Propositional Logic; Soundness and Completeness of Propositional Logic; Predicate Logic; Writing a Sentence into Clause Forms; Unification of Predicates; Robinson's Inference Rule; Different Types of Resolution; Semi-Decidability; Soundness and Completeness of Predicate Logic; Conclusions; PRINCIPLES OF LOGIC PROGRAMMING; Introduction to PROLOG Programming; Logic Programs - A Formal Definition; A Scene Interpretation Program; Illustrating Backtracking by flow of Satisfaction Diagrams; The SLD Resolution; Controlling Backtracking by CUT; The NOT Predicate; Negation as a Failure in Extended Logic Programs; Fixed Points in Non-Horn Clause Based Programs; Constraint Logic Programming; Conclusions; DEFAULT AND NON-MONOTONIC REASONING; Introduction; Monotonic versus Non-Monotonic Logic; Non-Monotonic Resoning Using NML-I; Fixed Points in Non-Monotonic Reasoning; Non-Monotonic Resoning Using NML-II; Truth Maintenance System; Default Reasoning; The Closed World Assumption; Circumscription; Auto-Epistemic Logic; Conclusions; STRUCTURED APPROACH TO KNOWLEDGE REPRESENTATION; Introduction; Semantic Nets; Inheritance in Semantic Nets; Manipulating Monotonic and Default Inheritance in Semantic Nets; Defeasible Reasoning in Semantic Nets; Frames; Inheritance in Tangled Frames; Petri nets; Conceptual Dependency; Scripts; Conclusions; DEALING WITH IMPRECISION AND UNCERTAINTY; Introduction; Probabilistic Reasoning; Certainty Factor Based Reasoning; Fuzzy Reasoning; Comparison of the Proposed Models; STRUCTURED APPROACH TO FUZZY REASONING; Introduction; Structural Model of Fuzzy FPN and Reachability Analysis; Behavioral Model of FPN and Stability Analysis; Forward Reasoning in FPN; Backward Reasoning in FPN; Bi-directional IFF Type Reasoning and Reciprocity; Fuzzy Modus Tollens and Duality; Non-Monotonic Reasoning in an FPN; Conclusions; REASONING WITH SPACE AND TIME; Introduction; Spatial Reasoning; Spatial Relationships among Components of an Object; Fuzzy Spatial Relationships among Objects; Temporal Reasoning by Situation Calculus; Propositional Temporal Logic; Interval Temporal Logic; Reasoning with Both Space and Time; Conclusions; INTELLIGENT PLANNING; Introduction; Planning with If-Add-Delete Operators; Least Commitment Planning; Hierarchical Task Network Planning; Multi-agent Planning; The Flowshop Scheduling Problem; Summary; MACHINE LEARNING TECHNIQUES; Introduction; Supervised Learning; Unsupervised Learning; Reinforcement Learning; Learning by Inductive Logic Programming; Computational Learning Theory; Summary; MACHINE LEARNING USING NEURAL NETS; Biological Neural Nets; Artificial Neural Nets; Topology of Artificial Neural Nets; Learning Using Neural Nets; The Back-Propagation Training Algorithm; Widrow-Hoff's Multi-Layers ADALINE Models; Hopfield Neural Net; Associative Memory; Fuzzy Neural Nets; Self-Organizing Neural Net; Adaptive Resonance Theory (ART); Applications of Artificial Neural Nets; GENETIC ALGORITHMS; Introduction; Deterministic Explanation of Holland's Observation; Stochastic Explanation of GA; The Markov Model for Convergence Analysis; Application of GA in Optimization Problems; Application of GA in Machine Learning; Applications of GA in Intelligent Search; Genetic Programming; Conclusions; REALIZING COGNITION USING FUZZY NEURAL NETS; Cognitive Maps; Learning by a Cognitive Map; The Recall in a Cognitive Map; Stability Analysis; Cognitive Learning with FPN; Applications in Autopilots; Generation of Control Commands by a Cognitive Map; Task Planning and Coordination; Putting it all Together; Conclusions and Future Directions; VISUAL PERCEPTION; Introduction; Low level Vision; Medium Level Vision; High Level Vision; Conclusions; LINGUISTIC PERCEPTION; Introduction; Syntactic Analysis; Augmented Transition Network Parsers; Semantic Interpretation by Case Grammar and Type Hierarchy; Discourse and Pragmatic Analysis; Applications of Natural Language Understanding; PROBLEM SOLVING BY CONSTRAINT SATISFACTION; Introduction; Formal Definitions; Constraint Propagation in Networks; Determining Satisfiability of CSP; Constraint Logic Programming; Geometric Constraint Satisfaction; Conclusions; ACQUISITION OF KNOWLEDGE; Introduction; Manual Approach for Knowledge Acquisition; Knowledge Fusion from Multiple Experts; Machine Learning Approach for Knowledge Acquisition; Knowledge Refinement by Hebbian Learning; Conclusions; VALIDATION, VERIFICATION AND MAINTENANCE ISSUES; Introduction; Valildation of Expert Systems; Verification of Knowledge Based System; Maintenance of Knowledge Based Systems; Conclusions; PARALLEL AND DISTRIBUTED ARCHITECTURE FOR INTELLIGENT SYSTEMS; Introduction; Salient Features of AI Machines; Parallelism in Heuristic Search; Parallelism at Knowledge Representational Level; Parallel Architecture for Logic Programming; Conclusions; CASE STUDY I: BUILDING A SYSTEM FOR CRIMINAL INVESTIGATION; An Overview of the Proposed Scheme; Introduction to Image Matching; Fingerprint Classification and Matching; Identification of the Suspects from Voice; Identification of the Suspects from Incidental Descriptions; Conclusions; CASE STUDY II: REALIZATION OF COGNITION FOR MOBILE ROBOTS; Mobile Robots; Scope of Realization of Cognition on Mobile Robots; Knowing the Robot's World; Types of Navigational Planning Problems; Offline Planning by Generalized Voronoi Diagram (GVD); Path Traversal Optimization Problem; Self-Orgainizing Map (SOM); Online Navigation by Modular Back-Propagation Neural Nets; Coordination among Sub-Modules in a Mobile Robot; An Application in a Soccer Playing Robot; The Expectations from the Readers; APPENDIX A: How to Run the Sample Programs?; APPENDIX B: Derivation of the Back-propagation Algorithm; APPENDIX C: Proof of the Theorems of Chapter 10; INDEX;
• Publisher Details: Place of publication not identified : CRC Press
• Publication Date: 2018
• Extent: 1 online resource (816 pages), (16 illustrations)
• Subjects: 006.3; Soft computing; Artificial intelligence; Brain -- Computer simulaion; Humans; Artificial intelligence; Soft computing; Electronic books; Electronic books
• Languages: English
• ISBNs: 9781351835626; 1351835629
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.