Curiosity-Driven Multi-Agent Exploration with Mixed Objectives

no code implementations • 29 Oct 2022 • Roben Delos Reyes, Kyunghwan Son, Jinhwan Jung, Wan Ju Kang, Yung Yi

First, we develop a two-headed curiosity module that is trained to predict the corresponding agent's next observation in the first head and the next joint observation in the second head.

QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning

3 code implementations • 14 May 2019 • Kyunghwan Son, Daewoo Kim, Wan Ju Kang, David Earl Hostallero, Yung Yi

We explore value-based solutions for multi-agent reinforcement learning (MARL) tasks in the centralized training with decentralized execution (CTDE) regime popularized recently.

Multi-agent Reinforcement Learning reinforcement-learning +2

Learning to Schedule Communication in Multi-agent Reinforcement Learning

1 code implementation • ICLR 2019 • Daewoo Kim, Sangwoo Moon, David Hostallero, Wan Ju Kang, Taeyoung Lee, Kyunghwan Son, Yung Yi

Many real-world reinforcement learning tasks require multiple agents to make sequential decisions under the agents' interaction, where well-coordinated actions among the agents are crucial to achieve the target goal better at these tasks.

Multi-agent Reinforcement Learning reinforcement-learning +2