Partial Observability
A classical problem setting in reinforcement learning and robotics in which the agent cannot directly obtain the complete state of the environment and can only infer it from noisy local sensor observations, requiring maintenance of uncertainty estimates such as belief states.
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Partial observability means that the agent cannot directly know the complete state of the environment and can only obtain local information through noisy sensor observations.
The paper identifies five physical constraints, including partial observability, irreversibility, and unverifiable outcomes, which together lead to fewer pre-fixed choices and less room for error correction.
All Facts (2)
Partial observability means that the agent cannot directly know the complete state of the environment and can only obtain local information through noisy sensor observations.
50%UnverifiedThe paper identifies five physical constraints, including partial observability, irreversibility, and unverifiable outcomes, which together lead to fewer pre-fixed choices and less room for error correction.
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