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Agents playing the iterated prisoner's dilemma learn to cooperate. It's usually not a dominant strategy to be entirely sociopathic when other players are involv
by marsten 6mo ago
Agents playing the iterated prisoner's dilemma learn to cooperate. It's usually not a dominant strategy to be entirely sociopathic when other players are involved.
- ehnto 6mo agoYou don't get that many iterations in the real world though, and if one of your first iterations is particularly bad you don't get any more iterations.
- cortesoft 6mo agoBut AI will train in the artificial world
- ehnto 6mo agoThey still fail in the real world, where a single failure can be highly consequential. AI coding is lucky it has early failure modes, pretty low consequence. But I don't see how that looks for an autonomous management agent with arbitrary metrics as goals. Anyone doing AI coding can tell you once an agent gets on the wrong path, it can get very confused and is usually irrecoverable. What does that look like in other contexts? Is restarting the process from scratch even possible in other types of work, or is that unique to only some kinds of work?
- naasking 6mo ago> You don't get that many iterations in the real world though True, for iterations between the same two players, but humans evolved the ability to communicate and so can share the results of past interactions through a network with other agents, aka a reputation. Thus any interaction with a new person doesn't start from a neutral prior.