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.

    Creators(s): Pattison, David ORCID logoORCID: https://orcid.org/0000-0003-0847-4422 and Long, Derek; Pattison, David, Long, Derek and Geib, Christopher
    Item type:Book Section
    ID code:47292
    Keywords:goal recognition, plan recognition, planning, intermediate, terminal plan states, bayesian goal recognition, Electronic computers. Computer science, Artificial Intelligence
    Subjects: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:31 Dec 2020 02:36
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/47292
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