Name
Abstract | ||
|---|---|---|
Real-time search algorithms need to address the deadlines imposed by applications like process control and robot navigation. Possible deadline violations should be predicted ahead of time to allow remedial actions to prevent the undesirable consequences of missing deadlines. The algorithms should also demonstrate progressively optimizing behavior. That is, they should improve the quality of the solutions as time constraints are relaxed. To successfully address these issues, a real-time search algorithm must address the central problem of choosing the proper values for its parameters, which control the time allocated to planning. The authors propose a new approach to determine the parameter values of a real-time search algorithm, in order to enable the algorithm to meet deadlines, exhibit progressively optimizing behavior, and to predict deadline violation prior to the deadline. They provide a theoretical and experimental characterization of the proposed algorithm |
Year | DOI | Venue |
|---|---|---|
1993 | 10.1109/TAI.1993.633961 | ICTAI |
Keywords | Field | DocType |
deadline violations,self-adjusting systems,process control,real-time search algorithm,progressively optimizing behavior,time constraints,resource allocation,self-adjusting real-time search,search problems,parameter values,remedial actions,robot navigation,real-time systems,application software,computer science,artificial intelligence,robots,search algorithm,navigation,time allocation,real time,real time systems | Search algorithm,Computer science,Resource allocation,Artificial intelligence,Process control,Robot,Application software,Machine learning,Real-time Search | Conference |
ISSN | ISBN | Citations |
1063-6730 | 0-8186-4200-9 | 1 |
PageRank | References | Authors |
0.40 | 7 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shashi Shekhar | 1 | 4352 | 1098.43 |
| Hamidzadeh Babak | 2 | 184 | 24.99 |