5 accepted papers
Cooperation among independent learning agents is desirable as it enables reaching collectively rewarding states. Recent work has shown that artificial agents can learn to act pro-socially without the need for predefined cooperative preferences or behavioural heuristics, provided that they can observ
Social dilemmas are an important benchmark to study the emergence of cooperation among autonomous learning agents and impressive results were recently achieved in two-player games by reinforcement learning agents equipped with a partner selection module. However, the same cannot be said for games on
If given the choice, what strategy should agents use to switch partners in strategic social interactions? While many analyses have been performed on specific switching heuristics, showing how and when these lead to more cooperation, no insights have been provided into which rule will actually be le…
The theoretical underpinnings of multiagent reinforcement learning has recently attracted much attention. In this work, we focus on the generalized social learning (GSL) protocol --- an agent interaction protocol that is widely adopted in the literature, and aim to develop an accurate theoretical m…
Modelling the dynamics of multi-agent learning has long been an important research topic, but all of the previous works focus on 2-agent settings and mostly use evolutionary game theoretic approaches. In this paper, we study an n-agent setting with n tends to infinity, such that agents learn their p…