This paper proposes the β-WoLF algorithm for multiagent reinforcement learning (MARL) in the stochastic games framework that uses an additional “advice” signal to inform agen...
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
Previous work in multiagent coordination has addressed the challenge of planning in domains where agents must optimize a global goal, while satisfying local resource constraints. ...
Emma Bowring, Zhengyu Yin, Rob Zinkov, Milind Tamb...
ort gives their abstracts. s of the position papers Recent Experiences with Code Generation and Task Automation Agents in Software Tools (J. Grundy, J. Hosking) As software grows i...