Research map / Multi-agent systems and games / Games and equilibria
Decentralized Q-learning in Zero-sum Markov Games
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use decentralized Q-learning with value estimates updated on a slower timescale than local Q estimates | Decentralized Q-learning · Discounted zero-sum Markov games | value-function convergence | Helped |
| Use the learning dynamics in self-play with temperature tending to zero | Decentralized Q-learning · Discounted zero-sum Markov games | Nash equilibrium exploitability | Helped |
| Use the learning dynamics against an asymptotically stationary opponent | Decentralized Q-learning · Discounted zero-sum Markov games | best-response value gap | Helped |
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