Multi-agent Covering Option Discovery based on Kronecker Product of Factor Graphs. (arXiv:2201.08227v1 [cs.MA])

Covering option discovery has been developed to improve the exploration of
reinforcement learning in single-agent scenarios with sparse reward signals,
through connecting the most distant states in the embedding space provided by
the Fiedler vector of the state transition graph. However, these option
discovery methods cannot be directly extended to multi-agent scenarios, since
the joint state space grows exponentially with the number of agents in the
system. Thus, existing researches on adopting options in multi-agent scenarios
still rely on single-agent …

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