Hierarchical Task Recognition and Planning in Smart Homes with Partial Observability
نویسندگان
چکیده
This paper proposes a goal recognition and planning algorithm, HTN-GRP-PO, to enable intelligent assistant agents to recognize older adults’ goals and reason about desired further steps. It will be used in a larger system aimed to help older adults with cognitive impairments to accomplish activities of daily living independently. The algorithm addresses issues including partial observability due to unreliable or missing sensors, concurrent goals, and incorrectly executed steps. The algorithm has a Hierarchical Task Network basis, which enables it to deal with partially ordered subtasks and alternative plans. We test on simulated cases of different difficulties. The algorithm works very well on simple cases, with accuracy close to 100%. Even for the hardest cases, the performance is acceptable when sensor reliabilities are above 0.95.
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