Clustering with reinforcement learning

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

Volumn 4881 LNCS, Issue , 2007, Pages 507-516

  Barbakh, Wesam ^a   Fyfe, Colin ^a  

^a UNIVERSITY OF THE WEST OF SCOTLAND   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

DATA STRUCTURES; OPTIMAL SYSTEMS; SUPERVISED LEARNING; TOPOLOGY;

NOVEL REWARD FUNCTIONS; SUPERVISED CLUSTERING; TOPOLOGY PRESERVING MAPPINGS;

REINFORCEMENT LEARNING;

EID: 38449114569     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-77226-2_52     Document Type: Conference Paper

References (12)

1. Barbakh, W.: The family of inverse exponential k-means algorithms. Computing and Information Systems 11(1), 1-10 (2007)
2. Barbakh, W., Crowe, M., Fyfe, C.: A family of novel clustering algorithms. In: Corchado, E., Yin, H., Botti, V., Fyfe, C. (eds.) IDEAL 2006. LNCS, vol. 4224, pp. 283-290. Springer, Heidelberg (2006)
3. Barbakh, W., Fyfe, C.: Performance functions and clustering algorithms. Computing and Information Systems 10(2), 2-8 (2006)
4. Barbakh, W., Fyfe, C.: Tailoring local and global interactions in clustering algorithms. Technical Report 40, School of Computing, University of Paisley (March 2007), ISSN 1461-6122
5. Bishop, C.M., Svensen, M., Williams, C.K.I.: Gtm: The generative topographic mapping. Neural Computation (1997)
6. Fyfe, C.: Two topographic maps for data visualization. Data Mining and Knowledge Discovery 14, 207-224 (2007)
7. Kaelbling, L.P., Littman, M.L., Moore, A.W.: Reinforcement learning: A survey. Journal of Artificial Intelligence Research 4, 237-285 (1996)
8. Kohonen, T.: Self-Organising Maps. Springer, Heidelberg (1995)
9. Likas, A.: A reinforcement learning approach to on-line clustering. Neural Computation (2000)
10. Sutton, R.S., Barto, A.G.: Reinforcement Learning: an Introduction. MIT Press, Cambridge (1998)
11. Williams, R.: Simple statistical gradient-following algorithms for connectionist reinforcement learning. Machine Learning 8, 229-256 (1992)
12. Williams, R.J., Pong, J.: Function optimization using connectionist reinforcement learning networks. Connection Science 3, 241-268 (1991)