2 papers
cs.LG2026
The PokeAgent Challenge: Competitive and Long-Context Learning at Scale
Seth Karten, Jake Grigsby, Tersoo Upaa +28
We present the PokeAgent Challenge, a large-scale benchmark for decision-making research built on Pokemon's multi-agent battle system and expansive role-playing game (RPG) environm…
cs.LG2024
MESA: Cooperative Meta-Exploration in Multi-Agent Learning through Exploiting State-Action Space Structure
Zhicheng Zhang, Yancheng Liang, Yi Wu +1
Multi-agent reinforcement learning (MARL) algorithms often struggle to find strategies close to Pareto optimal Nash Equilibrium, owing largely to the lack of efficient exploration.…