Unverified50% confidenceFactExact time
The algorithm directly implies that simple stochastic games can be solved in quasipolynomial time.
1
Sources
50%
Confidence
Long-term
Relevance
10/22/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedThe paper "Equilibrium Learning in Unbounded Stochastic Games with Gaussian Transitions" proposes a theoretical framework and algorithm for equilibrium learning in stochastic games with unbounded states.73% similarUnverifiedCommon means of mitigating the Sim-to-Real gap include domain randomization, system identification and online adaptation.66% similarUnverifiedComplex Monte Carlo simulations and nested stochastic models can leverage Spark's parallel processing capabilities to reduce runtime.66% similar
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