Interactive Swarm Optimization
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چکیده
Current optimization algorithms are designed for problems in which explicit fitness functions are provided. They can not be directly applied to problems where fitness functions do not exist, such as a situation where a user can interact with the computer by providing vague feedbacks instead of specific fitness. This paper proposes a population-based algorithm to solve such an optimization problem by combining the power of existing algorithms: Particle Swarm Optimization (PSO) and PopulationBased Incremental Learning (PBIL) to approximate a satisfying solution by construction of a series of "intermediate" ideal solutions that accumulate the identified characteristics the user may desire.
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