Paper Info
Title
Generating safe assumption-based plans for partially observable, nondeterministic domains
Abstract
Reactive planning using assumptions is a well-known approach to tackle complex planning problems for nondeterministic, partially observable domains. However, assumptions may be wrong; this may cause an assumption-based plan to fail. In general, it is not possible to decide at runtime whether an assumption has failed and is putting at danger the success of the plan; thus, plan execution has to be controlled taking into account every possible success-endangering assumption failure. The possibility of tracing such failures strongly depends on the actions performed by the plan. In this paper, focusing on a simple assumption language, we provide two main contributions. First, we formally characterize safe assumption-based plans, i.e. plans that not only succeed whenever the assumption holds, but also guarantee that any success-endangering assumption failure is traced by a suitable monitor. In this way, replanning may be triggered only when actually needed. Second, we extend the planner in a reactive platform in order to produce safe assumption-based plans. We experimentally show that safe assumption-based (re)planning is a good alternative to its unsafe counterpart, minimizing the need for replanning while retaining the efficiency in plan generation.
Year
Venue
Keywords
2004
AAAI
reactive platform,simple assumption language,plan generation,safe assumption-based plan,reactive planning,plan execution,possible success-endangering assumption failure,success-endangering assumption failure,generating safe assumption-based plan,complex planning problem,assumption-based plan,nondeterministic domain
Field
DocType
ISBN
Mathematical optimization,Observable,Nondeterministic algorithm,Computer science,Reactive planning,Planner,Tracing
Conference
0-262-51183-5
Citations 
PageRank 
References 
9
0.56
7
Authors
2
Name
Order
Citations
PageRank
Alexandre Albore1965.90
Piergiorgio Bertoli277546.89