C4.5: programs for machine learning
C4.5: programs for machine learning
Machine Learning
Incremental Induction of Decision Trees
Machine Learning
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Argument based machine learning
Artificial Intelligence
A persuasion dialog for gaining access to information
ArgMAS'07 Proceedings of the 4th international conference on Argumentation in multi-agent systems
Agent Support for Policy-Driven Collaborative Mission Planning
The Computer Journal
Learning policies through argumentation-derived evidence
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Practical strategic reasoning and adaptation in rational argument-based negotiation
ArgMAS'05 Proceedings of the Second international conference on Argumentation in Multi-Agent Systems
Argumentation strategies for plan resourcing
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Learning strategies for task delegation in norm-governed environments
Autonomous Agents and Multi-Agent Systems
Argumentation strategies for collaborative plan resourcing
ArgMAS'11 Proceedings of the 8th international conference on Argumentation in Multi-Agent Systems
Argumentation strategies for task delegation
EUMAS'11 Proceedings of the 9th European conference on Multi-Agent Systems
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An important and non-trivial factor for effectively developing and resourcing plans in a collaborative context is an understanding of the policy and resource availability constraints under which others operate. We present an efficient approach for identifying, learning and modeling the policies of others during collaborative problem solving activities. The mechanisms presented in this paper will enable agents to build more effective argumentation strategies by keeping track of who might have, and be willing to provide the resources required for the enactment of a plan. We argue that agents can improve their argumentation strategies by building accurate models of others' policies regarding resource use, information provision, etc. In a set of experiments, we demonstrate the utility of this novel combination of techniques through empirical evaluation, in which we demonstrate that more accurate models of others' policies (or norms) can be developed more rapidly using various forms of evidence from argumentation-based dialogue.