An aggregation-based extension of the DEC complexity measure yields new regret bounds for hybrid stochastic-adversarial RL and the first square-root-T regret for linear Q-star/V-star MDPs.
On the complexity of multi-agent decision making: From learning in games to partial monitoring
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Decision Making in Hybrid Environments: A Model Aggregation Approach
An aggregation-based extension of the DEC complexity measure yields new regret bounds for hybrid stochastic-adversarial RL and the first square-root-T regret for linear Q-star/V-star MDPs.