5 papers · 1 filter
RecBayes: Recurrent Bayesian Ad Hoc Teamwork in Large Partially Observable Domains
João G. Ribeiro, Yaniv Oren, Alberto Sardinha +2
This paper proposes RecBayes, a novel approach for ad hoc teamwork under partial observability, a setting where agents are deployed on-the-fly to environments where pre-existing te…
Solving General-Utility Markov Decision Processes in the Single-Trial Regime with Online Planning
Pedro P. Santos, Alberto Sardinha, Francisco S. Melo
In this work, we contribute the first approach to solve infinite-horizon discounted general-utility Markov decision processes (GUMDPs) in the single-trial regime, i.e., when the ag…
Implicit Repair with Reinforcement Learning in Emergent Communication
Fábio Vital, Alberto Sardinha, Francisco S. Melo
Conversational repair is a mechanism used to detect and resolve miscommunication and misinformation problems when two or more agents interact. One particular and underexplored form…
Distributed Value Decomposition Networks with Networked Agents
Guilherme S. Varela, Alberto Sardinha, Francisco S. Melo
We investigate the problem of distributed training under partial observability, whereby cooperative multi-agent reinforcement learning agents (MARL) maximize the expected cumulativ…
Networked Agents in the Dark: Team Value Learning under Partial Observability
Guilherme S. Varela, Alberto Sardinha, Francisco S. Melo
We propose a novel cooperative multi-agent reinforcement learning (MARL) approach for networked agents. In contrast to previous methods that rely on complete state information or j…