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EPRC is a leading institute in Europe for comparative research on public policy, with a particular focus on regional development policies. Spanning 30 European countries, EPRC research programmes have a strong emphasis on applied research and knowledge exchange, including the provision of policy advice to EU institutions and national and sub-national government authorities throughout Europe.

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Accurately determining intermediate and terminal plan states using bayesian goal recognition

Pattison, David and Long, Derek (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.