Team-symmetric games always have team-symmetric Nash equilibria solvable via linear complementarity problems, and the DelAC actor-critic MARL algorithm outperforms existing methods in simulations.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.MA 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
DelAC: A Multi-agent Reinforcement Learning of Team-Symmetric Stochastic Games
Team-symmetric games always have team-symmetric Nash equilibria solvable via linear complementarity problems, and the DelAC actor-critic MARL algorithm outperforms existing methods in simulations.