Adding a discrete 'communicate' action to a decentralized multi-robot exploration policy, with a reward that weights information gained by sharing, reduces exploration steps and overlap in simulated environments.
IEEE Transactions on Vehicular Technology 69(12), 14413–14423 (2020)
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Investigating the Impact of Communication-Induced Action Space on Exploration of Unknown Environments with Decentralized Multi-Agent Reinforcement Learning
Adding a discrete 'communicate' action to a decentralized multi-robot exploration policy, with a reward that weights information gained by sharing, reduces exploration steps and overlap in simulated environments.