Title :
Executable product models - The intelligent way
Author :
Kress, Markus ; Seese, Detlef
Author_Institution :
Univ. of Karlsruhe, Karlsruhe
Abstract :
Executable product models are an alternative approach in business process management with the objective to increase the flexibility during the execution of business processes in the service industry. This approach uses a special product model based on information dependencies comprising a compact representation of the set of all possible execution paths. To improve this approach and to take advantage from the flexibility provided we combine the multi-agent system with relational reinforcement learning and a genetic algorithm. We give an insight in the challenges of this approach and show how the efficiency is increased significantly.
Keywords :
commerce; genetic algorithms; learning (artificial intelligence); multi-agent systems; service industries; business process management; executable product models; genetic algorithm; multiagent system; relational reinforcement learning; service industry; Bills of materials; Data models; Design methodology; Genetic algorithms; Industrial relations; Learning; Multiagent systems; Process design; Production; Runtime;
Conference_Titel :
Systems, Man and Cybernetics, 2007. ISIC. IEEE International Conference on
Conference_Location :
Montreal, Que.
Print_ISBN :
978-1-4244-0990-7
Electronic_ISBN :
978-1-4244-0991-4
DOI :
10.1109/ICSMC.2007.4413598