Task scheduling with use of classifier systems

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1305, Issue , 1997, Pages 287-306

  SeredyŃski, Franciszek ^a  

^a INSTITUTE OF COMPUTER SCIENCE   (Poland)

Author keywords

[No Author keywords available]

Indexed keywords

GAME THEORY; GENETIC ALGORITHMS; LEARNING ALGORITHMS; MACHINE LEARNING; SCHEDULING; SCHEDULING ALGORITHMS;

CLASSIFIER SYSTEMS; DISTRIBUTED SCHEDULERS; EMERGENT BEHAVIORS; GAME THEORETICAL MODELS; LEARNING MACHINES; PARALLEL AND DISTRIBUTED ALGORITHMS; PARALLEL COMPUTER; THEORETICAL FRAMEWORK;

MULTI AGENT SYSTEMS;

EID: 0038855996     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/bfb0027182     Document Type: Conference Paper

References (18)

1. I. Ahmad, (ed.), Special Issue on Resource Management in Parallel and Distributed Systems with Dynamic Scheduling: Dynamic Scheduling, Concurrency: Practice and Experience, 7(7), 1995.
2. I. Ahmad and Y. Kwok, A Parallel Approach for Multiprocessing Scheduling, 9th Int. Parallel Processing Symposium, Santa Barbara, CA, April 25-28,1995
3. R. Axdrod, The Evolution of Strategies in the iterated Prisoners' Dilemma. In Davis L. (Ed.). Genetic Algorithms and Simulated Annealing. London, Pitman, 1987
4. J. Btaiewicz, K.H. Ecker, G. Schmidt, J. Wgglarz, Scheduling in Computer and Manufacturing Systems, Springer, 1994
5. L. B. Booker, D. E. Goldberg and J. H. Holland, Classifier Systems and Genetic Algorithms, Artificial Intelligence, 40, 1989
6. R. Bowden and S. F. Bullington, An Evolutionary Algorithm for Discovering Manufacturing Control Strategies, in Evolutionary Algorithms in Management Applications, J. Biethahn and V. Nissen (Eds.), Springer, 1995
7. M. Dorigo and U. Schnepf, Genetic-based Machine Learning and Behavior-based Robotics: a New Synthesis, IEEE Trans. on Systems, Man, and Cybernetics, v. 23, 1993
8. H. EI-Rewini and T. G. Lewis, "Schedtfling Parallel Program Tasks onto Arbitrary Target Machines", J. of Parallel and Distributed Computing 9, 138-153, 1990
9. H. E1-Rewini, T. G. Lewis, H. H. Ali, Task Scheduling in Parallel and Distributed Systems, PTR Prentice Hall, 1994.
10. D. B. Fogel, Evolving Behaviors in the Iterated Prisoner's Dilemma, Evolutionary Computation. vol. 1. N 1, 1993
11. D. E. Goldberg Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, Reading, MA, 1989
12. S. Matwin, T. Szapiro and K. Halgh, Genetic Algorithms Approach to a Negotiation Support System, IEEE Trans. on Systems, Man, and Cybernetics, v. 21, N1, 1991
13. M. Schwehm, T. Walter, Mapping and Scheduling by Genetic Algorithms, CONPAR 94 - VAPPVI, B. Buehberger and J. Volkert (eds.), LNCS 854, Springer, 1994
14. F. Seredynski, Loosely Coupled Distributed Genetic Algorithms, Parallel Problem Solving from Nature - PPSN III, Y. Davidor, H. -P. Schwefel and R. Märmer (eds.), LNCS 866, Springer, 1994
15. F. Seredynski and P. Frejlak, Genetic Algorithms Implementation of Process Migration Strategies, in Parallel Computing: Trends and Applications, G. R. Joubert, D. Trystram, F. J. Peters and D. J. Evans (eds.), Elsevier, 1994.
16. F. Seredynsld, P. Cichosz and G. P. Klebus, Learning Classifier Systems in Multi- Agent Environments, First IEE/IEEE Int. Conf. on Genetic Algorithms in Engineering Systems: Innovations and Applications (GALESIA '95), Shefield, UK, Sept. 11-14, 1995, IEE 1995.
17. F. Seredynski, Coevolutionary Game Theoretic Multi-Agent Systems, in Foundations of Intelligent Systems, Z. W. Ras and M. Michalewicz (eds.), LNAI 1079, Springer, 1996
18. B. Shirazi, A.R. Hurson and K.M. Kavi (eds.), Scheduling and Load Balancing in Parallel and Distributed Systems, IEEE Computer Society Press, 1995