Artificial Intelligence: Can Computers Think? |
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Page 62
... Control Processes , " Information and Control , vol . 4 , 1961 , pp . 246–249 . R. Bellman , " New Classes of Stochastic Control Processes , " Journal of Mathematical Analysis and Applications , vol . 22 , 1968 , pp . 602–617 . and the ...
... Control Processes , " Information and Control , vol . 4 , 1961 , pp . 246–249 . R. Bellman , " New Classes of Stochastic Control Processes , " Journal of Mathematical Analysis and Applications , vol . 22 , 1968 , pp . 602–617 . and the ...
Page 97
... processes , processes where cause and effect is assumed to hold . Let us now ... control process , and equate this operation with learning . One instinct ... control processes is the theory of dynamic programming . In animals , however ...
... processes , processes where cause and effect is assumed to hold . Let us now ... control process , and equate this operation with learning . One instinct ... control processes is the theory of dynamic programming . In animals , however ...
Page 131
... , but rather the proto - logic of an animal mind developed by evolution . 3. ALGORITHMS VS. DATA As an example of this allocation COMMUNICATION AND AMBIGUITY 131 Algorithms Introduction Communication as a Control Process.
... , but rather the proto - logic of an animal mind developed by evolution . 3. ALGORITHMS VS. DATA As an example of this allocation COMMUNICATION AND AMBIGUITY 131 Algorithms Introduction Communication as a Control Process.
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actual algorithm analog computer answer applications approach approximate policies arithmetic artificial intelligence assumptions average outcome behavior Bellman BIBLIOGRAPHY AND COMMENTS bility chapter chess COMMENTS Section complex concept consider Control Processes criterion function dealer determine deterministic device difficulty digital computer discussed draw a card drug Dynamic Programming effect example expected gain experience experimentation fast storage feasible fifteen puzzle foregoing functional equation fuzzy sets human idea important instinct interesting large number learning levels logic machine mathe mathematical analysis mathematical problems mathematical theory mathematician matical mean method minimize minimum Monte Carlo Method multistage decision process observe operations optimal play optimal policy particular path patient pattern recognition player possible precise proba probability distribution probability theory procedure puter puzzles question reasonable simple situations solve space stochastic approximation stochastic process structure talk tion transformation uncertainty unknown probability York Zadeh