Unlike previous approaches to plan recognition, PHATT is based on a model of plan execution.
The spread and introduction of resistant infections may not be preventable; but planning, recognition, and coordinated response can mitigate the consequences.
Millwall's academy has just been recommended for category two status under the Elite Performance Plan, recognition of its commitment to producing homegrown players for the first team.
For instance, diagnosis, natural language interpretation and plan recognition.
We present the PHATT algorithm for plan recognition.
Plan recognition algorithms output hypotheses about an agent's plans from its observed actions.
We present an approach to the plan recognition problem that is based on Bayesian probability theory.
In attempting to solve a plan recognition problem we first retrieve candidate explanations.
This paper describes a challenging plan recognition problem that arises in environments in which agents engage widely in exploratory behavior, and presents new algorithms for effective plan recognition in such settings.
The chapter provides an overview of plan recognition that is the inverse problem of plan synthesis.
We argue that the problem of plan recognition, inferring an agent's plan from observations, is largely a problem of inference under conditions of uncertainty.
