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- W2811360663 abstract "Decentralized decision-making requires the interaction of various local decision-makers in order to arrive at a global decision. Limited sensing capabilities at each local site can create ambiguities in a decision-making process at each local site. We argue that such ambiguities are of differing gradations. We propose a framework for decentralized decisionmaking (applied to decentralized control in particular) which allows computation of such ambiguity-gradations, and utilizes their knowledge in arriving at a global decision. Each local decision is tagged with a certain grade or level of ambiguity; zero being the minimum ambiguity level. A global decision is taken to be the same as a winning local decision, i.e., one having the minimum level of ambiguity. The computation of an ambiguity level for a local decision requires an assessment of the self-ambiguities as well as the ambiguities of the others, and an inference based up on such knowledge. In order to characterize the class of closed-loop behaviors achievable under the control of such an inference-based decentralized control, we introduce the notion of N-inference-observability, where N is an index representing the maximum ambiguity level of any winning local decision. We show that the C&PVD&Acoobservability is the same as the zero-inference-observability, whereas the conditional C&PVD&A-coobservability is the same as the unity-inference-observability. We also present examples of higher order inference-observable languages." @default.
- W2811360663 created "2018-07-10" @default.
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- W2811360663 date "2006-10-04" @default.
- W2811360663 modified "2023-10-14" @default.
- W2811360663 title "Inference-based Ambiguity Management in Decentralized Decision-Making: Decentralized Control of Discrete Event Systems" @default.
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- W2811360663 doi "https://doi.org/10.1109/cdc.2005.1582701" @default.
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