Nonetheless, the iterated prisoner's dilemma is a hard problem. There is a large strategy set, and good strategies must take account of the other players' strategies. Thus, unlike AI, which for much of its first generation focused on single agents, artificial morality began by focusing on a plurality of agents.
Ethics and Game Theory
One result of Axelrod's initiative was to unite ethics and game theory. On the one hand, game theory provides simple models of hard problems for ethics, such as the prisoner's dilemma. First, game theory forces expectations for ethics to be made explicit. Early work in this field (Danielson 1992) expected ethics to solve problems—such as cooperation in a one-play prisoner's dilemma—that game theory considers impossible. More recent work (Binmore 1994, Skyrms 1996) lower the expectations for ethics. Consider Axelrod's recommendation of the strategy tit-for-tat as a result of its relative success in his tournament. Because the game is iterated, tit-for-tat is not irrationally cooperative. However, its success shows only that tit-for-tat is an equilibrium for this game; it is rational to play tit-for-tat if enough others do. But game theory specifies that many—indeed infinitely many—strategies are equilibria for the iterated prisoner's dilemma.
This is a free page. This page contains 185 words. This
article contains 2,056 words (approx. 7 pages at 300
words per page).
Read the rest of this Article with our Artificial Morality Access Pass.
