A multi-agent intelligent environment for medical knowledge

  • Authors:

  • Rosa M Vicari;Cecilia D Flores;André M Silvestre;Louise J Seixas;Marcelo Ladeira;Helder Coelho

  • Affiliations:

  • Informatics Institute, Federal University of Rio Grande do Sul, Caixa Postal: 15064 91501-970, Porto Alegre, Rio Grande do Sul, Brazil;Informatics Institute, Federal University of Rio Grande do Sul, Caixa Postal: 15064 91501-970, Porto Alegre, Rio Grande do Sul, Brazil;Informatics Institute, Federal University of Rio Grande do Sul, Caixa Postal: 15064 91501-970, Porto Alegre, Rio Grande do Sul, Brazil;Post-graduate Course on Computer and Education, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil;Computer Science Department, University of Brasilia, Brasilia, Brazil;Informatics Department, Faculty of Science, University of Lisbon, Lisbon, Portugal

  • Venue:
  • Artificial Intelligence in Medicine
  • Year:
  • 2003

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Abstract

AMPLIA is a multi-agent intelligent learning environment designed to support training of diagnostic reasoning and modelling of domains with complex and uncertain knowledge. AMPLIA focuses on the medical area. It is a system that deals with uncertainty under the Bayesian network approach, where learner-modelling tasks will consist of creating a Bayesian network for a problem the system will present. The construction of a network involves qualitative and quantitative aspects. The qualitative part concerns the network topology, that is, causal relations among the domain variables. After it is ready, the quantitative part is specified. It is composed of the distribution of conditional probability of the variables represented. A negotiation process (managed by an intelligent MediatorAgent) will treat the differences of topology and probability distribution between the model the learner built and the one built-in in the system. That negotiation process occurs between the agents that represent the expert knowledge domain (DomainAgent) and the agent that represents the learner knowledge (LearnerAgent).