Minelli, Giovanni;
Musolesi, Mirco;
(2024)
CoMIX: A Multi-agent Reinforcement Learning Training Architecture for Efficient Decentralized Coordination and Independent Decision-Making.
Transactions in Machine Learning Research
(In press).
Preview |
Text
tmlr24_comix.pdf - Accepted Version Download (641kB) | Preview |
Abstract
Robust coordination skills enable agents to operate cohesively in shared environments, together towards a common goal and, ideally, individually without hindering each other’s progress. To this end, this paper presents Coordinated QMIX (CoMIX), a novel training framework for decentralized agents that enables emergent coordination through flexible policies, allowing at the same time independent decision-making at individual level. CoMIX models selfish and collaborative behavior as incremental steps in each agent’s decision process. This allows agents to dynamically adapt their behavior to different situations balancing independence and collaboration. Experiments using a variety of simulation environments demonstrate that CoMIX outperforms baselines on collaborative tasks. The results validate our incremental approach as effective technique for improving coordination in multi-agent systems.
| Type: | Article |
|---|---|
| Title: | CoMIX: A Multi-agent Reinforcement Learning Training Architecture for Efficient Decentralized Coordination and Independent Decision-Making |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | https://jmlr.org/tmlr/papers/ |
| Language: | English |
| Additional information: | © The Authors 2024. All TMLR submissions, from the time of submission to final publication, are licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10194560 |
Loading...
Loading...Loading...Loading...Archive Staff Only
 |
View Item |
