Reinforcement Learning for Heterogeneous Teams with PALO Bounds. - Roi Ceren; Prashant Doshi; Keyang He (CoRR, 2018)

Cooperative-Competitive Reinforcement Learning with History-Dependent Rewards. - Keyang He; Bikramjit Banerjee; Prashant Doshi (AAMAS, 2021)

Many Agent Reinforcement Learning Under Partial Observability. - Keyang He; Prashant Doshi; Bikramjit Banerjee (CoRR, 2021)

PALO bounds for reinforcement learning in partially observable stochastic games. - Roi Ceren; Keyang He; Prashant Doshi; Bikramjit Banerjee (Neurocomputing, 2021)

Reinforcement learning in many-agent settings under partial observability. - Keyang He; Prashant Doshi; Bikramjit Banerjee (UAI, 2022)

Latent Interactive A2C for Improved RL in Open Many-Agent Systems. - Keyang He; Prashant Doshi; Bikramjit Banerjee (CoRR, 2023)

Robust Individualistic Learning in Many-Agent Systems. - Keyang He; Prashant Doshi; Bikramjit Banerjee (PRIMA, 2024)

Modeling and reinforcement learning in partially observable many-agent systems. - Keyang He; Prashant Doshi; Bikramjit Banerjee (Auton. Agents Multi Agent Syst., 2024)