An agent-based approach for building complex software systems
Communications of the ACM
Business Dynamics
Resource-aware exploration of the emergent dynamics of simulated systems
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Developing Intelligent Agent Systems: A Practical Guide
Developing Intelligent Agent Systems: A Practical Guide
Co-Fields: A Physically Inspired Approach to Motion Coordination
IEEE Pervasive Computing
Case studies for self-organization in computer science
Journal of Systems Architecture: the EUROMICRO Journal - Special issue: Nature-inspired applications and systems
Toward nature-inspired computing
Communications of the ACM
Engineering Environment-Mediated Multi-Agent Systems
Towards a Methodology for Engineering Self-Organising Emergent Systems
Proceedings of the 2005 conference on Self-Organization and Autonomic Informatics (I)
Monitoring group behavior in goal-directed agents using co-efficient plan observation
AOSE'06 Proceedings of the 7th international conference on Agent-oriented software engineering VII
ProMAS'06 Proceedings of the 4th international conference on Programming multi-agent systems
Organizational and social concepts in agent oriented software engineering
AOSE'04 Proceedings of the 5th international conference on Agent-Oriented Software Engineering
Using the experimental method to produce reliable self-organised systems
Engineering Self-Organising Systems
A compositional approach to the stochastic dynamics of gene networks
Transactions on Computational Systems Biology IV
ESOA'05 Proceedings of the Third international conference on Engineering Self-Organising Systems
Testing in multi-agent systems
AOSE'10 Proceedings of the 10th international conference on Agent-oriented software engineering
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Conceiving applications as sets of autonomous agents is a prominent approach to the construction of complex distributed systems. Particularly attractive are decentralized application designs that enable adaptive, robust and scalable applications by allowing agents to self---organize. Tools to the construction of self---organizing MAS, e.g. decentralized coordination strategies, catch increasing attention in MAS research. However, their purposeful utilization challenges current development practices. The intended non---linear macroscopic dynamics hinder top---down designs on the drawing board and corresponding development procedures rely on sequences of manual system simulation. In order to stimulate methodical development and facilitate the validation of complex MAS by simulation, we present a systemic approach to the qualitative validation of macroscopic MAS dynamics. Describing MAS as dynamical systems enables developers to formulate hypotheses on the intended macroscopic MAS behaviors that guide system simulations. We discuss and exemplify how to (1) derive systemic models as well as hypotheses from MAS designs, (2) infer appropriate simulation settings to their validation and (3) interpret the obtained results. In addition, work in progress on the automation of both system simulations and their interpretation is outlined.