Topic
pomdp
VOiLA Framework Uses Diffusion Models to Cut Sampling Cost by Three Orders for POMDP Planning
Researchers present VOiLA, a framework that learns POMDP models for online planning under uncertainty using conditional diffusion models. The approach reduces sampling cost by nearly three orders of magnitude, matches or exceeds Recurrent Soft Actor Critic with less than 10% of training data, and generalizes better to unseen environments. Real-robot tests achieved 10/10 task success using models trained solely on simulation.
LLM-Driven World Simulation: New Framework Formalizes Game Master as Parameterized-Action POMDP
Researchers introduce Orchestrated Reality, a framework that formalizes LLM-driven game worlds as a Parameterized-Action POMDP. The approach uses a singleton orchestration agent called the Game Master to maintain persistent world state as canonical JSON entities, addressing the challenge of autonomous game engines where narrative voice asserts state without validated representation.