Synthesising Reward Machines for Cooperative Multi-Agent Reinforcement Learning
Giovanni Varricchione,
Natasha Alechina,
Mehdi Dastani
et al.
Abstract:Reward machines have recently been proposed as a means of encoding team tasks in cooperative multi-agent reinforcement learning. The resulting multi-agent reward machine is then decomposed into individual reward machines, one for each member of the team, allowing agents to learn in a decentralised manner while still achieving the team task. However, current work assumes the multi-agent reward machine to be given. In this paper, we show how reward machines for team tasks can be synthesised automatically from an… Show more
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