Diagnosis of Temporal Multiagent Plans (TMAPs) aims at identifying the causes of delays in achieving the plan goals. So far, approaches to TMAP diagno- sis have relied on an assumption that might not hold in many practical domains: action delays are independent of one another. In this paper we relax this assump- tion by allowing (indirect) dependencies among action delays. The diagnosis of a given TMAP is inferred by exploiting a qualitative Bayesian Network (BN), through which dependencies among actions delays, even performed by different agents, are captured. The BN, used to compute the heuristic function, drives a standard A* search, which finds all the most plausible explanations. Results of a preliminary experimental analysis show that the proposed Bayesian-based heuristic function is feasible.

Diagnosing Dependent Action Delays in Temporal Multiagent Plans

MICALIZIO, ROBERTO;TORTA, GIANLUCA
2013

Abstract

Diagnosis of Temporal Multiagent Plans (TMAPs) aims at identifying the causes of delays in achieving the plan goals. So far, approaches to TMAP diagno- sis have relied on an assumption that might not hold in many practical domains: action delays are independent of one another. In this paper we relax this assump- tion by allowing (indirect) dependencies among action delays. The diagnosis of a given TMAP is inferred by exploiting a qualitative Bayesian Network (BN), through which dependencies among actions delays, even performed by different agents, are captured. The BN, used to compute the heuristic function, drives a standard A* search, which finds all the most plausible explanations. Results of a preliminary experimental analysis show that the proposed Bayesian-based heuristic function is feasible.
The XXX SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence
Cambridge (UK)
10-12 December 2013
Research and Development in Intelligent Systems XXX
SPRINGER-VERLAG
157
171
9783319026206
http://www.bcs-sgai.org/ai2013/
Temporal Multiagent Plans; Model-based Diagnosis
Roberto Micalizio; Gianluca Torta
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2318/144504
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