The iterated prisoners' dilemma. 20 years on - download pdf or read online

By Graham Kendall

ISBN-10: 9812706976

ISBN-13: 9789812706973

In 1984, Robert Axelrod released a publication, bearing on the tale of 2 competitions which he ran, the place invited lecturers entered suggestions for the Iterated Prisoners hassle. The ebook, virtually two decades on, continues to be extensively learn and mentioned by means of teachers and most people. As a party of that landmark paintings, we now have recreated these competitions to have fun its twentieth anniversary, via back inviting lecturers to publish prisoners hassle thoughts. the 1st of those new competitions was once run in July 2004, and the second one in April 2005. Iterated Prisoners limitation: twenty years On primarily offers an replace of the Axelrod s booklet.

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Optimal strategies can be determined only if the strategy of the opponent is known. By means of reinforcement learning, model-based strategies with the ability of on-line identification of an opponent can be built [Sandholm and Crites (1996); Freund et al. (1995); Schmidhuber (1996)]. How can a player acquire a model of its opponent’s strategy? One possible source of information available for the player is the history of the game. Another possible source of information is observed games between the opponent and other agents.

Fogel D. (1993). Evolving Behaviours in the Iterated Prisoners Dilemma. Evolutionary Computation, 1, 1, pp. 77-97. Goldstein J. (1991). Reciprocity in Superpower Relations: An Empirical Analysis, International Studies Quarterly, 35, pp. 195-209. Maynard Smith J. (1982). Evolution and the Theory of Games (Cambridge University Press). Minas J. , Marlowe D. and Rawson H. (1960). Some Descriptive Aspects of Two-Person, Non-Zero-Sum Games, II, Journal of Conflict Resolution, 4, pp. 193-197. Nash J. (1950).

Selection is clearly an important genetic operator, but opinion is divided over the importance of crossover versus mutation. Some argue that crossover is the most important, while mutation is only necessary to ensure that potential solutions are not lost [Grefenstette, Ramsey and Schultz (1990); Wilson (1987)]. Others argue that crossover in a largely uniform population only serves to propagate innovations originally found by mutation, and in a non-uniform population crossover is nearly always equivalent to a very large mutation [Spears (1992)].

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The iterated prisoners' dilemma. 20 years on by Graham Kendall


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