Reaching agreements through argumentation: a logical model and implementation
Artificial Intelligence
Explanation component of software system
Crossroads - Special issue on object oriented programming
Automatically Selecting Strategies for Multi-Case-Base Reasoning
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
The Explanatory Power of Symbolic Similarity in Case-Based Reasoning
Artificial Intelligence Review
Learning collaboration strategies for committees of learning agents
Autonomous Agents and Multi-Agent Systems
On the comparison of theories: preferring the most specific explanation
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
d2isco: Distributed Deliberative CBR Systems with jCOLIBRI
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Distributed deliberative recommender systems
Transactions on computational collective intelligence I
Concept convergence in empirical domains
DS'10 Proceedings of the 13th international conference on Discovery science
Using personality to create alliances in group recommender systems
ICCBR'11 Proceedings of the 19th international conference on Case-Based Reasoning Research and Development
PISA: A framework for multiagent classification using argumentation
Data & Knowledge Engineering
Multi-agent based classification using argumentation from experience
Autonomous Agents and Multi-Agent Systems
eXiT*CBR.v2: Distributed case-based reasoning tool for medical prognosis
Decision Support Systems
Including social factors in an argumentative model for Group Decision Support Systems
Decision Support Systems
Hi-index | 0.00 |
This paper focuses of the group judgments obtained from a committee of agents that use deliberation. The deliberative process is realized by an argumentation framework called AMAL. The AMAL framework is completely based on learning from examples: the argument preference relation, the argument generation policy, and the counterargument generation policy are case-based techniques. For join deliberation, learning agents share their experience by forming a committee to decide upon some joint decision. We experimentally show that the deliberation in committees of agents improves the accuracy of group judgments. We also show that a voting scheme based on assessing the confidence of arguments improves the accuracy of group judgments than majority voting.