Title :
An algorithm for finding reliably schedulable plans
Author :
Takács, Balint ; Szita, István ; Lorincz, András
Author_Institution :
Dept. of Inf. Syst., Eotvos Lorand Univ., Budapest, Hungary
Abstract :
For interacting agents in time-critical applications, learning whether a subtask can be scheduled reliably is an important issue. The identification of sub-problems of this nature may promote e.g., planning, scheduling and segmenting in Markov decision processes. We define a subtask to be schedulable if its execution time has a small variance. We present an algorithm for finding such subtasks.
Keywords :
Markov processes; decision theory; learning (artificial intelligence); planning (artificial intelligence); scheduling; Markov decision processes; execution time scheduling; interacting agents; reliable scheduling plans; subproblems identification; time critical applications; Artificial intelligence; Cost function; Decision making; Information systems; Learning; Process planning; Scheduling algorithm; State-space methods; Stochastic processes; Time factors;
Conference_Titel :
Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
Print_ISBN :
0-7803-8359-1
DOI :
10.1109/IJCNN.2004.1380973
