Parallel and distributed intelligent systems

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PARALLEL AND DISTRIBUTED INTELLIGENT SYSTEMSArtificial Intelligence (AI) has both engineering and scientific goals: (a) to develop systems that have some form of intelligence, and (b) to understand intelligent behavior in systems and living organisms. Since biological systems embody a marked degree of parallel and distributed functioning, we believe that the architectures of intelligent systems and/or their implementations should also embody some forms of parallel and distributed computing. The systems should also exhibit some fundamental features of evolution in nature.The long-term objective of our work has been to develop efficient models, algorithms and implementations of parallel and distributed intelligent systems. Our goal has been not only to develop and experiment with new algorithms, but to develop operational software systems that can be employed in the real world as well. Whenever opportunities arise, the outcomes of our research will be commercialized and integrated in products.We propose: (a) to devise algorithms and software systems for efficient, effective, precise, semantic matching in e-Business, e-Learning and social networking environments, (b) to utilize knowledge (e.g. gene expression data, protein-protein interaction data and regulatory elements) about existing pathways of model organism to construct partial or complete regulatory networks for non-model organisms, and (c) to develop a semantically enriched dynamic knowledge delivery system for personal learning services.