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Found 2 papers, 2 papers with code
Robust Active Measuring under Model Uncertainty
Partial observability and uncertainty are common problems in sequential decision-making that particularly impede the use of formal models such as Markov decision processes (MDPs).
Act-Then-Measure: Reinforcement Learning for Partially Observable Environments with Active Measuring
In these models, actions consist of two components: a control action that affects the environment, and a measurement action that affects what the agent can observe.
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