Behavioral Experiments for Assessing the Abstract Argumentation Semantics of Reinstatement
Version of Record online: 3 NOV 2010
Copyright © 2010 Cognitive Science Society, Inc.
Volume 34, Issue 8, pages 1483–1502, November 2010
How to Cite
Rahwan, I., Madakkatel, M. I., Bonnefon, J.-F., Awan, R. N. and Abdallah, S. (2010), Behavioral Experiments for Assessing the Abstract Argumentation Semantics of Reinstatement. Cognitive Science, 34: 1483–1502. doi: 10.1111/j.1551-6709.2010.01123.x
- Issue online: 3 NOV 2010
- Version of Record online: 3 NOV 2010
- Received 21 July 2009; received in revised form 22 March 2010; accepted 31 March 2010
- Nonmonotonic reasoning;
- Defeasible reasoning;
Argumentation is a very fertile area of research in Artificial Intelligence, and various semantics have been developed to predict when an argument can be accepted, depending on the abstract structure of its defeaters and defenders. When these semantics make conflicting predictions, theoretical arbitration typically relies on ad hoc examples and normative intuition about what prediction ought to be the correct one. We advocate a complementary, descriptive-experimental method, based on the collection of behavioral data about the way human reasoners handle these critical cases. We report two studies applying this method to the case of reinstatement (both in its simple and floating forms). Results speak for the cognitive plausibility of reinstatement and yet show that it does not yield the full expected recovery of the attacked argument. Furthermore, results show that floating reinstatement yields comparable effects to that of simple reinstatement, thus arguing in favor of preferred argumentation semantics, rather than grounded argumentation semantics. Besides their theoretical value for validating and inspiring argumentation semantics, these results have applied value for developing artificial agents meant to argue with human users.