Emergent Diagnosis via Coalition Formation
IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
Self-Nonself Discrimination in a Computer
SP '94 Proceedings of the 1994 IEEE Symposium on Security and Privacy
How Do We Evaluate Artificial Immune Systems?
Evolutionary Computation
Advances in artificial immune systems
IEEE Computational Intelligence Magazine
A fuzzy logic based multi-agents controller
Expert Systems with Applications: An International Journal
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The goal of this work is to study emergent mechanisms that could possibly be embedded in multiagents systems in order to solve complex problems of distributed diagnosis. We assume the hypothesis that emergent functionalities share important structural and constitutive aspects, independently of the domain from which they emerge. The challenge of understanding self-organizing mechanisms (which allow that emergence occurs in nature) is important to develop systems able to better learn and adapt. Following such perspective we have been studying the human immune system (HIS) as a metaphor to solve problems where complexity and distribution are crucial constraints. Work in this paper reflects how characteristics from the HIS can be applied to conceive diagnosis systems. An application was implemented to student diagnosis in the context of an educational environment for learning basic programming skills.