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- W3178133733 abstract "The problem of combinatorial filter reduction arises from resource optimization in robots; it is one specific way in which automation can help to achieve minimalism, to build better robots. This paper contributes a new definition of filter minimization that is broader than its antecedents, allowing filters (input, output, or both) to be nondeterministic. This changes the problem considerably. Nondeterministic filters may re-use states to obtain more ‘behavior’ per vertex. We show that the gap in size can be significant (larger than polyno-mial), suggesting such cases will generally be more challenging than deterministic problems. Indeed, this is supported by the core complexity result established in this paper: producing nondeterministic minimizers is PSPACE-hard. The hardness separation for minimization existing between deterministic filter and automata, thus, fails to hold for the nondeterministic case." @default.
- W3178133733 created "2021-07-19" @default.
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- W3178133733 date "2022-05-23" @default.
- W3178133733 modified "2023-09-23" @default.
- W3178133733 title "On nondeterminism in combinatorial filters" @default.
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- W3178133733 doi "https://doi.org/10.1109/icra46639.2022.9812371" @default.
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