180 citations · 1.5k across the 49 of their papers we have counts for
4 papers · 2 filters
SCC-rFMQ Learning in Cooperative Markov Games with Continuous Actions
Chengwei Zhang, Xiaohong Li, Jianye Hao +5
Although many reinforcement learning methods have been proposed for learning the optimal solutions in single-agent continuous-action domains, multiagent coordination domains with c…
Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input
Angeliki Lazaridou, Karl Moritz Hermann, Karl Tuyls +1
The ability of algorithms to evolve or learn (compositional) communication protocols has traditionally been studied in the language evolution literature through the use of emergent…
Emergent Communication through Negotiation
Kris Cao, Angeliki Lazaridou, Marc Lanctot +3
Multi-agent reinforcement learning offers a way to study how communication could emerge in communities of agents needing to solve specific problems. In this paper, we study the eme…
SA-IGA: A Multiagent Reinforcement Learning Method Towards Socially Optimal Outcomes
Chengwei Zhang, Xiaohong Li, Jianye Hao +3
In multiagent environments, the capability of learning is important for an agent to behave appropriately in face of unknown opponents and dynamic environment. From the system desig…