C.I. Guinn, B. Bullard, R. Rahiminejad, E.C. Harris, W.J. Shipman, and E. Addision (USA)
Membrane computing, cost-based abduction and genetic algorithms.
This paper describes the first application of membrane computing to the cost-based abduction (CBA) optimization problem. Membrane systems are a class of distributed, massively parallel and non-deterministic data structures based on the biological metaphor of cells and cell processes. As such, algorithms based on these cell processes are suitable for implementation on massively parallel machines, and because of the localized nature of the communication between cells, load balancing is easier to predict and dynamically evaluate. Cost-based abduction is an important problem in reasoning in uncertainty with applications in medical diagnostics, natural language processing, belief revision, and automated planning. In this paper, we will describe a membrane architecture used to search for optimal solutions to cost-based abduction problems, compare the performance of this algorithm to other published techniques and present empirical results on the efficacy of various topologies of membrane structures.
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