Constructing Optimal Fuzzy Metric Trees for Agent Performance Evaluation

The field of multi-agent systems has reached a significant degree of maturity with respect to frameworks, standards and infrastructures. Focus is now shifted to performance evaluation of real-world applications, in order to quantify the practical benefits and drawbacks of agent systems. Our approach...

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Bibliographic Details
Main Authors: Dimou, Christos, Falelakis, Manolis, Symeonidis, Andreas L., Delopoulos, Anastasios, Mitkas, Pericles A.
Format: Conference Proceeding
Language:English
Subjects:
Aggregates
Application software
Computing methodologies > Artificial intelligence > Distributed artificial intelligence > Intelligent agents
Computing methodologies > Artificial intelligence > Knowledge representation and reasoning > Probabilistic reasoning
Computing methodologies > Artificial intelligence > Knowledge representation and reasoning > Vagueness and fuzzy logic
Current measurement
fuzzy logic
Fuzzy sets
Fuzzy systems
Intelligent agent
Intelligent agents
Multiagent systems
Organizing
performance evaluation
Process design
Software and its engineering > Software notations and tools > General programming languages > Language features > Frameworks
Testing
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Summary:The field of multi-agent systems has reached a significant degree of maturity with respect to frameworks, standards and infrastructures. Focus is now shifted to performance evaluation of real-world applications, in order to quantify the practical benefits and drawbacks of agent systems. Our approach extends current work on generic evaluation methodologies for agents by employing fuzzy weighted trees for organizing evaluation-specific concepts/metrics and linguistic terms to intuitively represent and aggregate measurement information.Furthermore, we introduce meta-metrics that measure the validity and complexity of the contribution of each metric in the overall performance evaluation. These are all incorporated for selecting optimal subsets of metrics and designing the evaluation process incompliance with the demands/restrictions of various evaluation setups, thus minimizing intervention by domain experts. The applicability of the proposed methodology is demonstrated through the evaluation of a real-world test case.
DOI:10.1109/WIIAT.2008.374