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What is Cognitive Diversity

Handbook of Research on Advancements of Swarm Intelligence Algorithms for Solving Real-World Problems
Cognitive diversity, which represents distribution of particles' “moving target”, measures the distribution of historical best positions for all particles. The measurement definition of cognitive diversity is the same as that of the position diversity except that it utilizes each particle's current personal best position instead of current position.
Published in Chapter:
Population Diversity of Particle Swarm Optimization Algorithm on Solving Single and Multi-Objective Problems
Shi Cheng (Shaanxi Normal University, China), Yuhui Shi (Southern University of Science and Technology, China), and Quande Qin (Shenzhen University, China)
DOI: 10.4018/978-1-7998-3222-5.ch014
Abstract
Premature convergence occurs in swarm intelligence algorithms searching for optima. A swarm intelligence algorithm has two kinds of abilities: the exploration of new possibilities and the exploitation of old certainties. The exploration ability means that an algorithm can explore more search places to increase the possibility that the algorithm can find good enough solutions. In contrast, the exploitation ability means that an algorithm focuses on the refinement of found promising areas. An algorithm should have a balance between exploration and exploitation, that is, the allocation of computational resources should be optimized to ensure that an algorithm can find good enough solutions effectively. The diversity measures the distribution of individuals' information. From the observation of the distribution and diversity change, the degree of exploration and exploitation can be obtained.
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Cognitive Diversity: Vital but Invisible
Diversity exhibited by individuals in terms of thinking and perceiving, processing and analysing and coming up with diverse ideas.
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