AI RESEARCH
Scaling Observation-aware Planning in Uncertain Domains
arXiv CS.AI
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ArXi:2605.22364v1 Announce Type: new Deciding which sensing capabilities to deploy on an agent in uncertain domains is a fundamental engineering challenge, in which one balances task achievability against the high costs of hardware and processing. This problem has previously been formalized as the Optimal Observability Problem (OOP), based on the well-known Partially Observable Marko Decision Process (POMDP) model for decision-making.