TY - GEN
T1 - On the benefits of argumentation-derived evidence in learning policies
AU - Emele, Chukwuemeka David
AU - Norman, Timothy J
AU - Guerin, Frank
AU - Parsons, Simon
PY - 2011/12/1
Y1 - 2011/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84857492858&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-21940-5_6
DO - 10.1007/978-3-642-21940-5_6
M3 - Published conference contribution
SN - 9783642219399
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 86
EP - 104
BT - Argumentation in Multi-Agent Systems - 7th International Workshop, ArgMAS 2010, Revised, Selected and Invited Papers
T2 - Seventh International Workshop on Argumentation in Multi-Agent Systems
Y2 - 10 May 2010 through 10 May 2010
ER -