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2015 | 25 | 3 | 439-454
Tytuł artykułu

A situation-based multi-agent architecture for handling misunderstandings in interactions

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
During interactions, system actors may face up misunderstandings when their local states contain inconsistent data about the same fact. Misunderstandings in interactions are likely to reduce interactivity performances (deviation or deadlock) or even affect overall system behavior. In this paper, we characterize misunderstandings in interactions between system actors (that may be human users or system agents) in interactive adaptive systems. To deal with such misunderstandings and ensure state consistency, we present an agent-based architecture and a scenario structuring approach. The system includes several agents devoted to scenario unfolding, plot adaptation and consistency management. Scenario structuring is based on the notion of a situation that is an elementary building block dividing the interactions between systems' actors into contextual scenes. This pattern supports not only scenario execution but consistency management as well. In order to organize and control interactions, the situation contextualizes interactions and activity of the system's actors. It also includes prevention and tolerance agent-based mechanisms to deal with the misunderstandings and their causes. We validate our consistency management mechanisms using Uppaal simulation and provide some experimental results to show the effectiveness of our approach on an online distance learning case study.
Rocznik
Tom
25
Numer
3
Strony
439-454
Opis fizyczny
Daty
wydano
2015
otrzymano
2014-06-30
poprawiono
2014-12-02
Twórcy
  • L3i Laboratory, University of La Rochelle, Avenue Michel Crépeau, 17042 La Rochelle Cedex 1, France
autor
  • L3i Laboratory, University of La Rochelle, Avenue Michel Crépeau, 17042 La Rochelle Cedex 1, France
  • L3i Laboratory, University of La Rochelle, Avenue Michel Crépeau, 17042 La Rochelle Cedex 1, France
Bibliografia
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  • Karlsson, B., Ciarlini, A.E.M., Feijo, B. and Furtado, A.L. (2006). Applying a plan-recognition/plan-generation paradigm to interactive storytelling, Workshop on AI Planning for Computer Games and Synthetic Characters (ICAPS 2006), Cumbria, UK, pp. 31-40.
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  • King, G.G. (2011). General aviation training for automation surprise, Journal of Professional Aviation Training & Testing Research 5(1): 46-51.
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  • Lebowitz, J. and Klug, C. (2011). Interactive Storytelling for Video Games: A Player-Centered Approach for Creating Memorable Character and Stories, Focal Press, Waltham, MA.
  • Lopez-Cozar, R., Callejas, Z. and Griol, D. (2010). Using knowledge about misunderstandings to increase the robustness of spoken dialogue systems, Knowledge-Based Systems 23(5): 471-485.
  • Magerko, B. and Laird, J.E. (2004). Mediating the tension between plot and interaction, AAAI Workshop Series: Challenges in Game Artificial Intelligence, San Jose, CA, USA, pp. 108-112.
  • Paul, R., Charles, D., McNeill, M. and McSherry, D. (2011). Adaptive storytelling and story repair in a dynamic environment, in M. Si et al. (Eds.), International Conference on Interactive Digital Storytelling (ICIDS), Lecture Notes in Computer Science, Vol. 7069, Springer, Berlin/Heidelberg, pp. 128-139.
  • Pham, P.T., Rabah, M. and Estraillier, P. (2011). Handling the misunderstanding in interactions: Definition and solution, International Conference on Software Engineering & Applications (SEA 2011), Singapore, pp. 47-52.
  • Pham, P.T., Rabah, M. and Estraillier, P. (2013). Agent-based architecture and situation-based scenario for consistency management, Federated Conference on Computer Science and Information Systems (FedCSIS 2013), Kraków, Poland, pp. 1065-1070.
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Typ dokumentu
Bibliografia
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