Artificial Intelligence: Can Computers Think? |
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Page 48
... uncertainty . 1. INTRODUCTION In this chapter we want to consider some examples of how the digital computer may be used for decision making under uncertainty . We regard decision making under uncertainty as one of the attributes of ...
... uncertainty . 1. INTRODUCTION In this chapter we want to consider some examples of how the digital computer may be used for decision making under uncertainty . We regard decision making under uncertainty as one of the attributes of ...
Page 60
... uncertainty . Our purpose was to show how a digital computer can do certain types of decision making under uncertainty . We have stressed several times that uncertainty is not equivalent to probability . Conse- quently , what we have ...
... uncertainty . Our purpose was to show how a digital computer can do certain types of decision making under uncertainty . We have stressed several times that uncertainty is not equivalent to probability . Conse- quently , what we have ...
Page 114
Can Computers Think? Richard Bellman. 9. UNCERTAINTY Let us now discuss some aspects of uncertainty . This phenomenon is part of the future . Indeed , we may define the future as what is uncer- tain . Where something is certain , we can ...
Can Computers Think? Richard Bellman. 9. UNCERTAINTY Let us now discuss some aspects of uncertainty . This phenomenon is part of the future . Indeed , we may define the future as what is uncer- tain . Where something is certain , we can ...
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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