Artificial Intelligence: Can Computers Think? |
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Page 41
Can Computers Think? Richard Bellman. choose state variables . Let us agree that the amounts of wine in each jug will specify the process . Next , we must see how decisions , actions , affect these state variables . It is easy to see the ...
Can Computers Think? Richard Bellman. choose state variables . Let us agree that the amounts of wine in each jug will specify the process . Next , we must see how decisions , actions , affect these state variables . It is easy to see the ...
Page 42
... variables . In this case , the numbers of canni- bals and missionaries on each bank and in the boat can be used as state variables . This yields a small number of possibilities . However , once again , we observe that we have a ...
... variables . In this case , the numbers of canni- bals and missionaries on each bank and in the boat can be used as state variables . This yields a small number of possibilities . However , once again , we observe that we have a ...
Page 97
... variables . This leads to the concept of a stochastic transformation T ( p , q , r ) . The point p1 = T ( p , q , r ) belongs to S when- ever p is in S , q is in D and r is a random variable in R. A choice of a sequence 41 , 42 ...
... variables . This leads to the concept of a stochastic transformation T ( p , q , r ) . The point p1 = T ( p , q , r ) belongs to S when- ever p is in S , q is in D and r is a random variable in R. A choice of a sequence 41 , 42 ...
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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