Diagnosis of plans and agents

Nico Roos*, Cees Witteveen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

Abstract

We discuss the application of Model-Based Diagnosis in (agent-based) planning. Here, a plan together with its executing agent is considered as a system to be diagnosed. It is assumed that the execution of a plan can be monitored by making partial observations of the results of actions. These observations are used to explain the observed deviations from the plan by qualifying some action instances that occur in the plan as behaving abnormally. Unlike in standard model-based diagnosis, however, in plan diagnosis we cannot assume that actions fail independently. We focus on two sources of dependencies between failures: such failings may occur as the result of malfunctioning of the executing agent or may be caused by dependencies between action instances occurring in a plan. Therefore, we introduce causal rules that relate health states of the agent and health states of actions to abnormalities of other action instances. These rules enable us to determine the underlying causes of plan failing and to predict future anomalies in the execution of actions.
Original languageEnglish
Title of host publicationMulti-Agent Systems and Applications IV
EditorsMichael Pechoucek, Paolo Petta, László Zsolt Varga
PublisherSpringer
Pages357-366
Number of pages10
Volume3690
DOIs
Publication statusPublished - 2005

Publication series

SeriesLecture Notes in Computer Science

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