A Distributed Artificial Intelligence View for Complex Problem Solving - Three Case Studies in Computer Vision, Biomedical Imagery and Knowledge Acquisition

Abstract

There has recently been considerable international interest in the use of Distributed Artificial Intelligence Techniques for Knowledge-based System Development. The use of Multi-Agent architectures has several advantages such as modularizing problem-solving knowledge, alleviating the complexity of developing knowledgebased systems by distributing knowledge amongst a group of cooperating agents, or facilitating the integration of heterogeneous knowledge schemes and reasoning mechanisms. However, a crucial question is to analyze how to work at the "right" level of knowledge when designing multi-agent architectures for complex problem solving. To achieve this, the nature of knowledge and distinct facets that knowledge can adopt are reviewed and analyzed which permits us to propose a coherent knowledge model. In the second part, a brief description of the MAPS programming environment will be given based on the knowledge model previously proposed. Then, three case studies are addressed whic..