Name
Abstract | ||
|---|---|---|
The Classical Iterated Prisoner's Dilemma (CIPD) is used to study the evolution of cooperation. We show, with a genetic approach, how basic ideas could be used in order to generate automatically a great numbers of strategies. Then we show some results of ecological evolution on those strategies, with the description of the experimentations we have made. Our main purpose is to find an objective method to evaluate strategies for the CIPD. Finally we use the former results to add a new argument confirming that there is, in orde r to be good, an infinite gradient in the level of complexity in structure of s trategies. |
Year | DOI | Venue |
|---|---|---|
1998 | 10.1007/BFb0040757 | Evolutionary Programming |
Keywords | Field | DocType |
classical iterated prisoner,complete classes,genetics | Intelligent agent,Evolutionary algorithm,Computer science,Prisoner's dilemma,Artificial intelligence,Dilemma,Objective method,Iterated function,Reinforcement learning | Conference |
ISBN | Citations | PageRank |
3-540-64891-7 | 17 | 2.88 |
References | Authors | |
1 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bruno Beaufils | 1 | 20 | 5.08 |
| Jean-Paul Delahaye | 2 | 325 | 54.60 |
| Philippe Mathieu | 3 | 139 | 28.72 |