Abstract
The analysis of an agent or agent communities combining advanced methods of visualization with traditional AI techniques is presented in this paper. However this approach can be used for arbitrary Multi-Agent System (MAS), it was primarily developed to analyse systems falling into Artificial Life domain. Traditional methods are becoming insufficient as MAS are becoming more complex and therefore novel approaches are needed. Our approach builds upon various techniques to deliver means for assessment on multiple levels ranging from single agent to overall properties of an agent community. Our visualization tools suite utilizes novel visualization methods together with traditional AI techniques such as sensitivity analysis and clustering. Among others it offers visualization of many agent’s parameters along time, correspondence between current/previous states (of an agent community), resulting behaviour, grouping of agents based on dominant properties etc. This transparent approach emphasizes MAS dynamics through automatic discovery of its tendency. Agent position inside virtual environment together with overview over the whole time interval adds strong contextual information to analysis. Position in our understanding is not limited to geometrical meaning, but covers also the space of dynamically changing constraints for action selection. A simulated artificial life environment with intelligent agents has been used as a test bed. We have selected this particular domain because our long-term goal is to model life as it could be so as to understand life, as we know it.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Szekely, P., Rogers, C.M.: Interfaces for Understanding Multi-Agent Behavior. In: Proc. ACM Conf. on Intelligent User Interfaces, Santa Fe New Mexico USA, pp. 161–166 (2001)
Beneš, B., Espinosa, E.: Modeling Virtual Ecosystems with Proactive Guidance of Agents. In: IEEE Computer Animation and Social Agents, New Bruncwick USA (2003) (to appear)
Allbeck, J., Badler, N.: Toward Representing Agent Behaviors Modified by Personality and Emotion. In: Workshop on Embodied Conversational Agents, Bologna, Italy (2002)
Schroeder, M., Noy, P.: Multiagent Visualisation Based on Multivariate Data. In: Proc. 5th International Conf. on Autonomous Agents, Montreal Canada, pp. 85–91 (2001)
Chatterjee, S., Hadi, A.S.: Sensitivity Analysis in Linear Regression. John Wiley & Sons, New York (1988)
Inselberg, A., Dimsdale, B.: Parallel Coordinates: A Tool for Visualizing Multivariate Relations. Plenum Publishing Corporation, New York (1991)
Havre, S., Hetzler, E., et al.: ThemeRiver: Visualizing Thematic Changes in Large Document Collections. IEEE Trans. on Visualization and Computer Graphics 8(1) (2002)
Nahodil, P., Kadlecek, D., Rehor, D., Slavík, P.: Transparent Visualization of Multi-Agent Systems. In: Proc. 4th International Carpathian Control Conference, High Tatras Slovakia, pp. 723–727 (2003)
Rehor, D., Kadlecek, D., Slavík, P., Nahodil, P.: VAT – An Approach to Multi-Agent System Vizualization. In: IASTED International Conference on Visualization, Imaging and Image Processing, Benalmadena Spain, pp. 849–854 (2003)
Kadlecek, D., Nahodil, P.: New Hybrid Architecture in Artificial Life Simulation. In: Kelemen, J., Sosík, P. (eds.) ECAL 2001. LNCS (LNAI), vol. 2159, pp. 143–146. Springer, Heidelberg (2001)
McFarland, D., Bosser, U.: Intelligent Behavior in Animals and Robots. MIT Press, Cambridge (1993)
Ferber, J.: Multi Agent Systems. An Introduction to Distributed Artificial Intelligence. Addison-Wesley, Reading (1999)
Kadlecek, D., Rehor, D., Nahodil, P., Slavík, P.: Analysis of Virtual Agent Communities by Means of AI Techniques and Visualization. In: Intelligent Virtual Agents, pp. 274–282. Springer, Heidelberg (2003)
Slavík, P., Míkovec, Z., Hrdlicka, F.: Special Problems of Visualization in a Specific Environment. In: East-West-Vision, pp. 269–270. Österreichische Computer Gesellschaft, Wien (2002)
Nahodil, P., Petrus, M.: Behaviour Co-ordination in Multi-Robot Group. In: Proceedings of the International IASTED Conference MIC, February 18-21, pp. 464–468. ACTA Press, Innsbruck (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Nahodil, P., Slavík, P., Rehor, D., Kadlecek, D. (2004). Dynamic Analysis of Agents’ Behaviour – Combining ALife, Visualization and AI. In: Omicini, A., Petta, P., Pitt, J. (eds) Engineering Societies in the Agents World IV. ESAW 2003. Lecture Notes in Computer Science(), vol 3071. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25946-6_22
Download citation
DOI: https://doi.org/10.1007/978-3-540-25946-6_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22231-6
Online ISBN: 978-3-540-25946-6
eBook Packages: Springer Book Archive