Anastassacos, N;
Musolesi, M;
(2019)
Towards Decentralized Reinforcement Learning Architectures for Social Dilemmas.
In:
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems.
(pp. pp. 1776-1777).
ACM: Montreal, Canada.
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Abstract
Multi-agent reinforcement learning has received significant interest in recent years notably due to the advancements made in deep reinforcement learning which have allowed for the developments of new architectures and learning algorithms. In this extended abstract we present our initial efforts towards the development of decentralized architectures for multi-agent systems in order to understand and model societies. More specifically, using social dilemmas as the training ground, we present a novel learning architecture, Learning through Probing (LTP), where agents utilize a probing mechanism to incorporate how their opponent's behavior changes when an agent takes an action.
| Type: | Proceedings paper |
|---|---|
| Title: | Towards Decentralized Reinforcement Learning Architectures for Social Dilemmas |
| Event: | AAMAS '19 |
| Location: | Montreal, CANADA |
| Dates: | 13 May 2019 - 17 May 2019 |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | https://dl.acm.org/doi/10.5555/3306127.3331915 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Science & Technology, Technology, Computer Science, Theory & Methods, Computer Science, Multi-agent Systems, Reinforcement Learning, Cooperation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10090575 |
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