Learning Partially Observable Deterministic Action Models
نویسندگان
چکیده
منابع مشابه
Learning Partially Observable Deterministic Action Models
We present the first tractable, exact solution for the problem of identifying actions’ effects in partially observable STRIPS domains. Our algorithms resemble Version Spaces and Logical Filtering, and they identify all the models that are consistent with observations. They apply in other deterministic domains (e.g., with conditional effects), but are inexact (may return false positives) or inef...
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ژورنال
عنوان ژورنال: Journal of Artificial Intelligence Research
سال: 2008
ISSN: 1076-9757
DOI: 10.1613/jair.2575