The method based on Q-learning path planning in migrating workflow

Proceedings - 2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer, MEC 2013

Volumn , Issue , 2013, Pages 2204-2208

  Xiao, Song ^a   Wang, Xiaolin ^a  

^a SHANDONG UNIVERSITY   (China)

Author keywords

Migrating path; Mobile agent; Reinforcement learning; Social acquaintance network

Indexed keywords

MOTION PLANNING; REINFORCEMENT LEARNING; WORK SIMPLIFICATION;

GOAL-ORIENTED; MIGRATING INSTANCE; MIGRATING PATH; MIGRATING WORKFLOW; NETWORK ENVIRONMENTS; ORDERED SET; PARTIALLY OBSERVABLE ENVIRONMENTS; TARGET ORIENTED;

MOBILE AGENTS;

EID: 84918536300     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/MEC.2013.6885412     Document Type: Conference Paper

References (8)

1. Zeng G, Dang Y. The Study of Migrating Workflow Based on the Mobile Computing Paradiam[J]. Chinese Journal of Computers, 2003, 26(10): 1343-1349.
2. Cheng J, Zeng G, He H. Research on Migrating Instance Path Planning in Migrating Workflow System[J]. Journal of Frontiers of Computer Science and Technology, 2008, 2(6): 658-665.
3. Zhang JZeng G, Han F. Path Search and Optimization in Goal-oriented Migrating Workflow[J]. Application Research of Computers, 2008, 25(9): 2623-2624.
4. Cheng J, Zeng G A Greedy Particle Swarm Optimization Algorithm for Workplace Planning in Migrating Workflow[C]. Natural Servputation, 2008. ICNC'08. 2008, 6: 407-411.
5. Sutton R S, Barto A G Reinforcement learning: An introduction[M]. Cambridge: MIT press, 1998.
6. Boguñá M, Pastor-Satorras R, Díaz-Guilera A et al. Models of social networks based on social distance attachment[J]. Physical Review E, 2004, 70(5): 056122.
7. Puterman M L. Markov decision processes: discrete stochastic dynamic programming[M]. Wiley-Interscience, 2009
8. Tokic M. Adaptive ε-greedy exploration in reinforcement learning based on value differences[M]. KI 2010: Advances in Artificial Intelligence. Springer Berlin Heidelberg, 2010: 203-210.