Abstract
Collaborative decision making among agents in a team is a complex activity, and tasks to achieve individual objectives may conflict in a team context. A number of argumentation-based models have been proposed to address the problem, the rationale being that the revelation of background information and constraints can aid in the discovery and resolution of conflicts. To date, however, no empirical studies have been conducted to substantiate these claims. In this paper, we discuss a model, grounded on argumentation schemes, that captures potential conflicts due to scheduling and causality constraints, and individual goals and norms. We evaluate this model in complex collaborative planning problems and show that such a model facilitates the sharing of relevant information pertaining to plan, goal and normative conflicts. Further, we show that this focussed information sharing leads to more effective conflict resolution, particularly in the most challenging problems.
Original language | English |
---|---|
Title of host publication | ECAI 2012 |
Subtitle of host publication | 20th European Conference on Artificial Intelligence |
Editors | L. De Raedt, C. Bessiere, D. Dubois, P. Doherty, P. Frasconi, F. Heintz, P. Lucas |
Publisher | IOS Press |
Pages | 756-761 |
Number of pages | 6 |
ISBN (Print) | 978-1-61499-097-0 |
DOIs | |
Publication status | Published - Aug 2012 |
Publication series
Name | Frontiers in Artificial Intelligence and Applications |
---|---|
Volume | 242 |
Keywords
- Multi-agent systems
- Argumentation
Fingerprint
Dive into the research topics of 'An empirical study of argumentation schemes in deliberative dialogue'. Together they form a unique fingerprint.Datasets
-
Models of argument for deliberative Dialogue in Complex Domains: Data Bundle
Toniolo, A. (Creator), Norman, T. J. F. (Creator), Sycara, K. P. (Creator) & Oren, N. (Data Manager), University of Aberdeen, 1 Sept 2015
DOI: 10.20392/de145553-9e73-42ef-8f0b-f5c1565b3457
Dataset