Learning When to Collaborate among Learning Agents

@inproceedings{Ontan2001LearningWT,
  title={Learning When to Collaborate among Learning Agents},
  author={Santiago Onta{\~n}{\'o}n and Enric Plaza},
  booktitle={ECML},
  year={2001}
}
Multiagent systems o er a new paradigm where learning techniques can be useful. We focus on the application of lazy learning to multiagent systems where each agents learns individually and also learns when to cooperate in order to improve its performance. We show some experiments in which CBR agents use an adapted version of LID (Lazy Induction of Descriptions), a CBR method for classi cation. We discuss a collaboration policy (called Bounded Counsel) among agents that improves the agents… CONTINUE READING
18 Citations
13 References
Similar Papers

References

Publications referenced by this paper.
Showing 1-10 of 13 references

On the importance of similitude: An entropy-based assessment

  • E. Plaza, R. L opez de M antaras, E. Armengol
  • Advances in Case-Based Reasoning,
  • 1996
1 Excerpt

Stolfo . A comparative evaluation of voting and metalearning on partitioned data

  • L. K. Hansen
  • Proc . 12 th International Conference on Machine…
  • 1995

Similar Papers

Loading similar papers…