A note on the learning effect in multi-agent optimization

Expert Systems with Applications

Volumn 38, Issue 5, 2011, Pages 5974-5980

  Janiak, Adam ^a   Rudek, Radosław ^b  

^a WROCLAW UNIVERSITY OF TECHNOLOGY   (Poland)

^b WROCLAW UNIVERSITY OF ECONOMICS   (Poland)

Author keywords

Learning effect; Reinforcement learning; Routing; Scheduling

Indexed keywords

INDUSTRIAL SYSTEMS; ITS EFFICIENCIES; LEARNING ABILITIES; LEARNING EFFECTS; MAKESPAN MINIMIZATION; MULTI-AGENT; NP-HARD; ROUTING; SCHEDULING PROBLEM; SERVICES SECTORS; SINGLE MACHINES; TOTAL TRANSMISSION;

INTERNET; MULTI AGENT SYSTEMS; OPTIMIZATION; REINFORCEMENT LEARNING; SCHEDULING ALGORITHMS;

LEARNING ALGORITHMS;

EID: 79151486009     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2010.11.024     Document Type: Article

References (28)

1. D. Biskup A state-of-the-art review on scheduling with learning effects European Journal of Operational Research/ 188 2008 315 329
2. J.A. Boyan, and M.L. Littman Packet routing in dynamically changing networks: a reinforcement learning approach J.D. Cowan, G. Tesauro, J. Alspector, Advances in neural information processing systems Vol. 6 1994 Morgan Kaufmann Publishers Los Altos 671 678
3. L. Buoniu, R. Babuška, and B. De Schutter A comprehensive survey of multiagent reinforcement learning IEEE Transactions On Systems, Man, And Cybernetics - Part C: Applications And Reviews 38 2008 156 172
4. W.J. Dally, and C.L. Seitz The torus routing chip Journal of Distributed Computing 1 1986 187 196
5. M. Dietzfelbinger, A. Karlin, K. Mehlhorn, F. Meyer auf der Heide, H. Rohnert, and C.L. Tarjan Dynamic perfect hashing: Upper and lower bounds SIAM Journal on Computing 23 1994 738 761
6. R.L. Graham, E.L. Lawler, J.K. Lenstra, and A.H.G. Rinnooy Kan Optimization and approximation in deterministic sequencing and scheduling: A survey Annals of Discrete Mathematics 5 1979 287 326
7. D. Jackson Technological change, the learning curve, and profitability 1998 Edward Elgar Northampton, Mass.
8. A. Janiak, and R. Rudek The learning effect: Getting to the core of the problem Information Processing Letters 103 2007 183 187
9. A. Janiak, and R. Rudek A new approach to the learning effect: Beyond the learning curve restrictions Computers & Operations Research 35 2008 3727 3736
10. A. Janiak, and R. Rudek Experience based approach to scheduling problems with the learning effect IEEE Transactions on Systems, Man, and Cybernetics - Part A 39 2009 344 357
11. R.M. Karp Reducibility among combinatorial problems R.E. Miller, J.W. Thatcher, Complexity of computer computations 1972 Plenum Press 85 103
12. W.-H. Kuo, and D.-L. Yang Single-machine group scheduling with a time-dependent learning effect Computers & Operations Research 33 2006 2099 2112
13. W.-C. Lee, C.-C. Wu, and M.-F. Li A single-machine bi-criterion learning scheduling problem with release times Expert Systems with Applications 36 2009 10295 10303
14. G. Mosheiov Parallel machine scheduling with a learning effect Journal of the Operational Research Society 52 2001 1 5
15. G. Mosheiov Scheduling problems with a learning effect European Journal of Operational Research 132 2001 687 693
16. R. Pagh, and F.F. Rodler Cuckoo hashing Journal of Algorithms 51 2004 22 144
17. Rudek, R.; Koszałka, L.; & Poźniak-Koszałka, I. (2006). A multi-agent approach to routing in computer networks. In Proceedings of the 18th international conference on system engineering (pp. 413-418).
18. R. Rudek, L. Koszałka, and I. Poźniak-Koszałka Introduction to multi-agent modified Q-learning routing for computer networks Proceedings of advances industrial conference on telecommunications/ service assurance with partial and intermittent resource conference/ e-learning on telecommunications workshop 2005 IEEE Computer Society Press 408 413
19. R. Rudek, I. Poźniak-Koszałka, L. Koszałka, O. Haas, and K.J. Burnham System with database for evaluating routing algorithms in computer networks Proceedings of the 14th IASTED international conference on applied simulation and modelling 2005 ACTA Press 192 197
20. R.S. Sutton, and A.G. Barto Reinforcement learning: An introduction 1998 MIT Press Cambridge
21. E.L. Thorndike Animal intelligence: An experimental study of the associative process in animals The Psychological Review: Monograph Supplements 2 1898 1 109
22. L.L. Thurstone The learning curve equation Psychological Monograph 26 1919 1 51
23. Toksari, M. D.; & Güner, E. (in press). The common due-date early/tardy scheduling problem on a parallel machine under the effects of time-dependent learning and linear and nonlinear deterioration. Expert Systems with Applications. doi:10.1016/j.eswa.2009.05.014.
24. Toksari, M. D.; leyen, S. K.; Güner, E.; & Bayko, Ö. F. (in press). Assembly line balancing problem with deterioration tasks and learning effect. Expert Systems with Applications. doi:10.1016/j.eswa.2009.06.005.
25. H. White Artificial neural networks: Approximation and learning theory 1992 Blackwell Cambridge
26. S. Whiteson, and P. Stone Adaptive job routing and scheduling Engineering Applications of Artificial Intelligence 17 2004 855 869
27. T.P. Wright Factors affecting the cost of airplanes Journal of Aeronautical Sciences 3 1936 122 128
28. L.E. Yelle The learning curve: Historical review and comprehensive study Decision Science 10 1979 302 328