Tesauro G. Programming backgammon using self-teaching neural nets. Artificial Intelligence, 134:181--199, 2002. Home/Search Document Not in Database Summary Related Articles Check |
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Developments On Monte Carlo Go - Bouzy (2003) (1 citation) (Correct)
....of Monte Carlo lies in the use of the random generator function, and theoretically, Monte Carlo refers to [Fishman, 1996] Monte Carlo methods have already been used in computer games. In incomplete information games, such as poker [Billings et al. 2002] scrabble [Sheppard, 2002] and backgammon [Tesauro, 2002], this approach is natural: because the information possessed by your opponent is hidden, you want to simulate this information. In complete information games, the idea of replacing complete information by randomized information is less natural. Nevertheless, this is not the first time that Monte ....
Tesauro, G. (2002). Programming backgammon using self-teaching neural nets. Artificial Intelligence vol 134, pages 181--199.
The Challenge of Poker - Billings, Davidson, Schaeffer.. (2001) (7 citations) (Correct)
....relatively low variance in the previous gure may again be a result of both programs being close to maximal gains against that particular level of opposition. 34 that relatively simple rollouts can achieve a level of play comparable to the original neural network evaluation function of TD Gammon [36, 37]. 3. In bridge, the cards of other players are hidden information. A simulation consists of assigning cards to the opponents in a manner that is consistent with the bidding. The hand is then played out and the result determined. Repeated deals are played out to decide which play produces the ....
G. Tesauro. Programming backgammon using self-teaching neural nets. Articial Intelligence, 2001. Elsewhere in this issue.
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Tesauro G. Programming backgammon using self-teaching neural nets. Artificial Intelligence, 134:181--199, 2002.
Artificial Intelligence 134 (2002) 201--240 - The Challenge Of (2002) (165 citations) (Correct)
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G. Tesauro, Programming backgammon using self-teaching neural nets, Artificial Intelligence 134 (2002) 181--199 (this issue).
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Gerald Tesauro. Programming Backgammon Using Self-Teaching Neural Nets. Arti cial Intelligence, 134(1-2):181-199, 2002.
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Gerald Tesauro (2002) Programming backgammon using self-teaching neural nets. Artificial Intelligence 134, 181-199.
Scripting the Game of Lemmings with a Genetic Algorithm - Kendall, Spoerer (2004) (Correct)
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Tesauro G. Programming backgammon using self-teaching neural nets. Artificial Intelligence, 134:181--199, 2002.
Opponent Modeling in Poker: Learning and Acting in a Hostile and .. - Davidson (2002) (1 citation) (Correct)
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G. Tesauro. Programming backgammon using self-teaching neural nets. Arti- cial Intelligence, 134(1-2):181-199, 2002.
A Distributed Reinforcement Learning Approach to Pattern.. - Abramson, Wechsler (2003) (Correct)
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G. Tesauro. Programming backgammon using self-teaching neural nets. Artificial Intelligence Journal, 134(1-2):181--199, January 2002.
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