Article

Tracking causality by visualization of multi-agent interactions using causality graphs

Authors:

Guillermo Vigueras,

Juan A. BotiaAuthors Info & Claims

ProMAS'07: Proceedings of the 5th international conference on Programming multi-agent systems

Pages 190 - 204

Published: 15 May 2007 Publication History

Abstract

Programming multi-agent systems is a hard task and requires tools to assist in the process of testing, validation and verification of both MAS specifications and source code. In this paper, we propose the use of causality graphs, adapted to the context of debugging multi-agents systems, to track causality of events produced in interactions among agents in a group. We believe that simple sequence diagrams are not enough to visually track what are the predecessors or causes of a given new event (i.e. an unexpected message or the observation that a message did not came). We propose this kind of graph as an alternative. We redefine the concept of causality graph for this particular field and propose an algorithm for generation of such a graph.

References

[1]

Bordini, R., Fisher, M., Pardavila, C., Wooldridge, M.: Model checking agentspeak

[2]

Bordini, R.H., Dastani, M., Dix, J., EI Fallah-Seghrouchni, A. (eds.): Multi-Agent Programming: Languages, Platforms and Applications. In: Multiagent Systems, Artificial Societies, and Simulated Organizations, vol. 15. Springer, Heidelberg (2005).

Digital Library

[3]

Botia, J.A., Hernansaez, J.M., Gomez-Skarmeta, A.F.: Towards an approach for debugging mas through the analysis of acl messages. Computer Systems Science and Engineering (July 20, 2005).

[4]

De Wolf, T., Holvoet, T.: Towards a methodology for engineering self-organising emergent systems. Self-Organization and Autonomic Informatics 135, 18-34 (2005).

Digital Library

[5]

Dror Zernitk, M.S., Malki, D.: Using visualization tools to understand concurrency. IEEE Softw 9, 87-92 (1992).

Digital Library

[6]

FIPA. Fipa acl message structure specification. Technical report, FIPA (2002).

[7]

FIPA. Fipa contract net interaction protocol specication. Technical report, FIPA (2002).

[8]

Garg, V.K.: Concurrent and Distributed Computing in Java. Wiley, IEEE Press (2004).

Digital Library

[9]

Botia, J.M.H.J.A., Gomez-Skarmeta, A.F.: On the application of clustering techniques to support debugging large-scale multi-agent systems. In: Programming Multi-Agent Systems Workshop AAMAS, Hakodate, Japan (2006).

Digital Library

[10]

Lam, D.N., Barber, K.S.: Comprehending agent software. In: AAMAS 2005: Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems, pp. 586-593. ACM Press, New York (2005).

Digital Library

[11]

Lamport, L.: Time, clocks, and the ordering of events in a distributed system. Commun. ACM 21(7), 558-565 (1978).

Digital Library

[12]

Ndumu, D.T., Nwana, H.S., Lee, L.C., Collis, J.C.: Visualising and debugging distributed multi-agent systems. In: ACM Press (ed.) AGENTS 1999: Proceedings of the third annual conference on Autonomous Agents, pp. 326-333 (1999).

Digital Library

[13]

Raynal, M., Singhal, M.: Logical time: Capturing causality in distributed systems. Computer 29(2), 49-56 (1996).

Digital Library

[14]

von Staa Roberta Coelho, A., Kulesza, U., Lucena, C.: Unit testing in multi-agent systems using mock agents and aspects. In: SELMAS 2006: Proceedings of the 2006 international workshop on Software engineering for large-scale multi-agent systems, pp. 83-90. ACM Press, New York (2006).

Digital Library

[15]

Schroeder, M., Noy, P.: Multi-agent visualisation based on multivariate data. In: Proceedings of the Fifth International Conference on Autonomous Agents, Montreal, Canada, ACM Press, New York (2001).

Digital Library

Cited By

Higashino MOsaki SOtagaki STakahashi KKawamura TSugahara KWeippl EIndrawan-Santiago MSteinbauer MKotsis GKhalil I(2013)Debugging Mobile Agent SystemsProceedings of International Conference on Information Integration and Web-based Applications & Services10.1145/2539150.2539261(667-670)Online publication date: 2-Dec-2013
https://dl.acm.org/doi/10.1145/2539150.2539261
Sudeikat JRenz W(2009)Qualitative modeling of MAS dynamicsProceedings of the 10th international conference on Agent-oriented software engineering10.5555/1965954.1965962(80-93)Online publication date: 11-May-2009
https://dl.acm.org/doi/10.5555/1965954.1965962
Dastani MBrandsema JDubel AMeyer J(2009)Debugging BDI-based multi-agent programsProceedings of the 7th international conference on Programming multi-agent systems10.5555/1928304.1928318(151-169)Online publication date: 10-May-2009
https://dl.acm.org/doi/10.5555/1928304.1928318
Show More Cited By

Index Terms

Tracking causality by visualization of multi-agent interactions using causality graphs
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
      1. Multi-agent systems
2. Software and its engineering
  1. Software creation and management
    1. Software verification and validation
      1. Software defect analysis
        Software testing and debugging

Index terms have been assigned to the content through auto-classification.

Recommendations

Complexity results for structure-based causality

We give a precise picture of the computational complexity of causal relationships in Pearl's structural models, where we focus on causality between variables, event causality, and probabilistic causality. As for causality between variables, we consider ...
Granular Causality Applications: Using Part-of Relations for Discovering Causality

Causal markers, syntactic structures and connectives have been the sole identifying features for automatically extracting causal relations in natural language discourse. However, various connectives such as "and", prepositions such as "as", and other ...
Causality Detection for Efficient Multi-Agent Reinforcement Learning
AAMAS '23: Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems

When learning a task as a team, some agents in Multi-Agent Reinforcement Learning (MARL) may fail to understand their true impact in the performance of the team. Such agents end up learning sub-optimal policies, demonstrating undesired lazy behaviours. ...

Comments

Information & Contributors

Information

Published In

cover image Guide Proceedings

ProMAS'07: Proceedings of the 5th international conference on Programming multi-agent systems

May 2007

266 pages

ISBN:354079042X

Editors:
Mehdi Dastani
Utrecht University, The Netherlands
,
Amal El Fallah Seghrouchni
University of Paris VI, France
,
Alessandro Ricci
Università di Bologna, Cesena, Italy
,
Michael Winikoff
RMIT University, Melbourne, Australia

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 15 May 2007

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

5
Total Citations
View Citations
3
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 26 Jul 2024

Other Metrics

View Author Metrics

Citations

Cited By

Higashino MOsaki SOtagaki STakahashi KKawamura TSugahara KWeippl EIndrawan-Santiago MSteinbauer MKotsis GKhalil I(2013)Debugging Mobile Agent SystemsProceedings of International Conference on Information Integration and Web-based Applications & Services10.1145/2539150.2539261(667-670)Online publication date: 2-Dec-2013
https://dl.acm.org/doi/10.1145/2539150.2539261
Sudeikat JRenz W(2009)Qualitative modeling of MAS dynamicsProceedings of the 10th international conference on Agent-oriented software engineering10.5555/1965954.1965962(80-93)Online publication date: 11-May-2009
https://dl.acm.org/doi/10.5555/1965954.1965962
Dastani MBrandsema JDubel AMeyer J(2009)Debugging BDI-based multi-agent programsProceedings of the 7th international conference on Programming multi-agent systems10.5555/1928304.1928318(151-169)Online publication date: 10-May-2009
https://dl.acm.org/doi/10.5555/1928304.1928318
Peng WKrueger WGrushin ACarlos PManikonda VSantos MSierra CCastelfranchi CDecker KSichman J(2009)Graph-based methods for the analysis of large-scale multiagent systemsProceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 110.5555/1558013.1558088(545-552)Online publication date: 10-May-2009
https://dl.acm.org/doi/10.5555/1558013.1558088
Serrano EGómez-Sanz JBotía JPavón J(2009)Intelligent data analysis applied to debug complex software systemsNeurocomputing10.1016/j.neucom.2008.10.02572:13-15(2785-2795)Online publication date: 1-Aug-2009
https://dl.acm.org/doi/10.1016/j.neucom.2008.10.025

View Options

View options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Table of Contents