Develops infinite-horizon stationary robust mean-field games incorporating distributional uncertainty, proves equilibrium existence via fixed-point on contractive Bellman operator, gives convergent algorithm, and derives finite-population approximation bounds under contractive regime.
arXiv preprint arXiv:1807.03858 , year=
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Mind Dreamer uses active causal intervention via an adversarial initial-state generator and relay value functions to untether imagination in MBRL, claiming 1.67x average and up to 8.8x sparse-reward speedups over DreamerV3.
Offline RL promises to extract high-utility policies from static datasets but faces fundamental challenges that current methods only partially address.
citing papers explorer
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Stationary Robust Mean-Field Games under Model Mismatches
Develops infinite-horizon stationary robust mean-field games incorporating distributional uncertainty, proves equilibrium existence via fixed-point on contractive Bellman operator, gives convergent algorithm, and derives finite-population approximation bounds under contractive regime.
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Mind Dreamer: Untethering Imagination via Active Causal Intervention on Latent Manifolds
Mind Dreamer uses active causal intervention via an adversarial initial-state generator and relay value functions to untether imagination in MBRL, claiming 1.67x average and up to 8.8x sparse-reward speedups over DreamerV3.
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Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
Offline RL promises to extract high-utility policies from static datasets but faces fundamental challenges that current methods only partially address.