Accurately determining intermediate and terminal plan states using bayesian goal recognition
Pattison, David and Long, Derek; Pattison, David and Long, Derek and Geib, Christopher, eds. (2011) Accurately determining intermediate and terminal plan states using bayesian goal recognition. In: GAPRec 2011. Proceedings of the First Workshop on Goal, Activity and Plan Recognition. ICAPS, pp. 32-37.
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Abstract
Goal Recognition concerns the problem of determining an agent's final goal, deduced from the plan they are currently executing (and subsequently being observed). The set of possible goals or plans to be considered are commonly stored in a library, which is then used to propose possible candidate goals for the agent's behaviour. Previously, we presented AUTOGRAPH - a system which removed the need for a goal or plan library, thus making any problem solvable without the need to construct such a structure. In this paper, we discuss IGRAPH, which improves upon its predecessor by utilising Bayesian inference to determine both terminal and intermediate goals/states which the agent being observed is likely to pass through.
ORCID iDs
Pattison, David ORCID: https://orcid.org/0000-0003-0847-4422 and Long, Derek; Pattison, David, Long, Derek and Geib, Christopher-
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Item type: Book Section ID code: 47292 Dates: DateEvent12 June 2011PublishedSubjects: Science > Mathematics > Electronic computers. Computer science Department: Faculty of Science > Computer and Information Sciences Depositing user: Pure Administrator Date deposited: 02 Apr 2014 11:18 Last modified: 11 Nov 2024 14:54 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/47292