Mixed Cooperative-Competitive Communication Using Multi-Agent Reinforcement Learning
| Autor: | Simon Vanneste, Steven Latre, Wesley Van Wijnsberghe, Peter Hellinckx, Siegfried Mercelis, Astrid Vanneste, Kevin Mets |
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| Rok vydání: | 2021 |
| Předmět: |
Computer. Automation
FOS: Computer and information sciences Computer Science - Machine Learning Computer science Private communication Machine Learning (cs.LG) Human–computer interaction Mass communications Reinforcement learning Computer Science - Multiagent Systems Observability Differentiable function Training period Multiagent Systems (cs.MA) |
| Zdroj: | Advances on P2P, Parallel, Grid, Cloud and Internet Computing ISBN: 9783030898984 Advances on P2P, Parallel, Grid, Cloud and Internet Computing : proceedings of the 16th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC-2021) |
| DOI: | 10.48550/arxiv.2110.15762 |
| Popis: | By using communication between multiple agents in multi-agent environments, one can reduce the effects of partial observability by combining one agent's observation with that of others in the same dynamic environment. While a lot of successful research has been done towards communication learning in cooperative settings, communication learning in mixed cooperative-competitive settings is also important and brings its own complexities such as the opposing team overhearing the communication. In this paper, we apply differentiable inter-agent learning (DIAL), designed for cooperative settings, to a mixed cooperative-competitive setting. We look at the difference in performance between communication that is private for a team and communication that can be overheard by the other team. Our research shows that communicating agents are able to achieve similar performance to fully observable agents after a given training period in our chosen environment. Overall, we find that sharing communication across teams results in decreased performance for the communicating team in comparison to results achieved with private communication. |
| Databáze: | OpenAIRE |
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