An Empirical Study on the Practical Impact of Prior Beliefs over Policy Types

Abstract: Many multiagent applications require an agent to learn quickly how to interact with previously unknown other agents. To address this problem, researchers have studied learning algorithms which compute posterior beliefs over a hypothesised set of policies, based on the Continue reading

E-HBA: Using Action Policies for Expert Advice and Agent Typification

Abstract: Past research has studied two approaches to utilise pre-defined policy sets in repeated interactions: as experts, to dictate our own actions, and as types, to characterise the behaviour of other agents. In this work, we bring these complementary views Continue reading