Under-informed momentum in PSO
Pages 13 - 14
Abstract
Particle Swarm Optimization is fundamentally a stochastic algorithm, where each particle takes into account noisy information from its own history as well as that of its neighborhood. Though basic information-theoretic principles would suggest that less noise indicates greater certainty, the momentum term is simultaneously the least directly-informed and the most deterministically applied. This dichotomy suggests that the typically confident treatment of momentum is misplaced, and that swarm performance can benefit from better-motivated processes that obviate momentum entirely.
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Index Terms
- Under-informed momentum in PSO
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Published: 12 July 2014
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