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Artificial intelligence. Robotics. Simulation. Graphics --- Programming languages (Electronic computers) --- Langages de programmation --- Syntax --- Semantics --- Syntaxe --- Sémantique --- 681.3*D31 --- 681.3*F3 --- 681.3*F32 --- 681.3*F4 --- Formal definitions and theory: semantics; syntax (Programming languages)--See also {681.3*D21}; {681.3*F31}; {681.3*F32}; {681.3*F42}; {681.3*F43} --- Logics and meanings of programs (Theory of computation) --- Semantics of programming languages: algebraic approaches to semantics; denotational semantics; operational semantics (Logics and meanings of programs)--See also {681.3*D31} --- Mathematical logic and formal languages (Theory of computation) --- 681.3*F4 Mathematical logic and formal languages (Theory of computation) --- 681.3*F32 Semantics of programming languages: algebraic approaches to semantics; denotational semantics; operational semantics (Logics and meanings of programs)--See also {681.3*D31} --- 681.3*F3 Logics and meanings of programs (Theory of computation) --- 681.3*D31 Formal definitions and theory: semantics; syntax (Programming languages)--See also {681.3*D21}; {681.3*F31}; {681.3*F32}; {681.3*F42}; {681.3*F43} --- Syntax. --- Semantics. --- Informatique --- Computer science

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Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

Reinforcement learning. --- Reinforcement learning (Machine learning) --- Machine learning. --- Reinforcement learning --- 681.3*I26 --- 681.3*I2 --- 681.3*I2 Artificial intelligence. AI --- Artificial intelligence. AI --- 681.3*I26 Learning: analogies; concept learning; induction; knowledge acquisition; language acquisition; parameter learning (Artificial intelligence)--See also {681.3*K32} --- Learning: analogies; concept learning; induction; knowledge acquisition; language acquisition; parameter learning (Artificial intelligence)--See also {681.3*K32} --- Machine learning --- Reinforcement (Psychology) --- Learning classifier systems --- Apprentissage par renforcement (Intelligence artificielle) --- Learning, Machine --- Artificial intelligence --- Machine theory --- Monograph

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Microprocessor Programming and Applications for Scientists and Engineers

Programming --- Microprocessors --- 6502 (Microprocessor) --- Microprocesseurs --- Programmation --- Programming. --- 681.3*C53 --- 681.3*C53 Microcomputers: microprocessors (Computer system implementation) --- Microcomputers: microprocessors (Computer system implementation)

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The need to transmit and store massive amounts of data reliably and without error is a vital part of modern communications systems. Error-correcting codes play a fundamental role in minimising data corruption caused by defects such as noise, interference, crosstalk and packet loss. This book provides an accessible introduction to the basic elements of algebraic codes, and discusses their use in a variety of applications. The author describes a range of important coding techniques, including Reed-Solomon codes, BCH codes, trellis codes, and turbocodes. Throughout the book, mathematical theory is illustrated by reference to many practical examples. The book was first published in 2003 and is aimed at graduate students of electrical and computer engineering, and at practising engineers whose work involves communications or signal processing.

Data transmission systems --- Signal processing --- Data communication systems --- Transmission of data --- Digital communications --- Electronic data processing --- Electronic systems --- Information theory --- Telecommunication systems --- Mathematical models. --- Mathematics. --- Data transmission systems - Mathematical models --- Signal processing - Mathematics --- 681.3*E4 --- 681.3*I42 --- 681.3*I42 Compression (coding): approximate methods; exact coding (Image processing)--See also {681.3*E4} --- Compression (coding): approximate methods; exact coding (Image processing)--See also {681.3*E4} --- 681.3*E4 Coding and information theory: data compaction and compression; formal modelsof communication; nonsecret encoding schemes--See also {681.3*H11} --- Coding and information theory: data compaction and compression; formal modelsof communication; nonsecret encoding schemes--See also {681.3*H11} --- Mathematical models --- Mathematics

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Logic programming --- Programmation logique --- Congresses. --- Congrès --- Computer Science --- Engineering & Applied Sciences --- 681.3*I22 --- 681.3*F31 --- 681.3*D11 --- 681.3*D16 --- 681.3*D24 --- 681.3*F41 --- Automatic programming: automatic analysis of algorithms; program modification; program synthesis; program transformation; program verification (Artificialintelligence)--See also {681.3*D12}; {681.3*F31} --- Specifying anf verifying and reasoning about programs: assertions; invariants; mechanical verification; pre- and post-conditions (Logics and meanings of programs)--See also {681.3*D21}; {681.3*D24}; {681.3*D31}; {681.3*E1} --- Applicative (functional) programming --- Programming techniques: Logic programming --- Program verification: assertion checkers; correctness proofs; reliability; validation (Software engineering)--See also {681.3*F31} --- Mathematical logic: computability theory; computational logic; lambda calculus; logic programming; mechanical theorem proving; model theory; proof theory;recursive function theory--See also {681.3*F11}; {681.3*I22}; {681.3*I23} --- 681.3*F41 Mathematical logic: computability theory; computational logic; lambda calculus; logic programming; mechanical theorem proving; model theory; proof theory;recursive function theory--See also {681.3*F11}; {681.3*I22}; {681.3*I23} --- 681.3*D24 Program verification: assertion checkers; correctness proofs; reliability; validation (Software engineering)--See also {681.3*F31} --- 681.3*D11 Applicative (functional) programming --- 681.3*F31 Specifying anf verifying and reasoning about programs: assertions; invariants; mechanical verification; pre- and post-conditions (Logics and meanings of programs)--See also {681.3*D21}; {681.3*D24}; {681.3*D31}; {681.3*E1} --- 681.3*I22 Automatic programming: automatic analysis of algorithms; program modification; program synthesis; program transformation; program verification (Artificialintelligence)--See also {681.3*D12}; {681.3*F31} --- Computer science. --- Computer programming. --- Computer logic. --- Mathematical logic. --- Artificial intelligence. --- Computer Science. --- Logics and Meanings of Programs. --- Artificial Intelligence (incl. Robotics). --- Programming Techniques. --- Mathematical Logic and Formal Languages. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Algebra of logic --- Logic, Universal --- Mathematical logic --- Symbolic and mathematical logic --- Symbolic logic --- Mathematics --- Algebra, Abstract --- Metamathematics --- Set theory --- Syllogism --- Computer science logic --- Logic, Symbolic and mathematical --- Computers --- Electronic computer programming --- Electronic digital computers --- Programming (Electronic computers) --- Coding theory --- Informatics --- Science --- Programming --- Logic design. --- Artificial Intelligence. --- Design, Logic --- Design of logic systems --- Digital electronics --- Electronic circuit design --- Logic circuits --- Switching theory --- Logic programming - Congresses. --- Machine theory. --- Computer Science Logic and Foundations of Programming. --- Formal Languages and Automata Theory. --- Abstract automata --- Abstract machines --- Automata --- Mathematical machine theory --- Algorithms --- Recursive functions --- Robotics