Do Random and Chaotic Sequences Really Cause Different PSO Performance? Further Results
{Paul Moritz N\"orenberg, Hendrik Richter

TL;DR
This paper investigates whether chaotic and random sequences lead to different PSO performance, finding that distribution rather than chaos or randomness primarily influences results.
Contribution
It provides a detailed analysis showing that the underlying distribution, not chaos or randomness, mainly affects PSO performance, challenging previous assumptions.
Findings
Distribution is the main factor influencing PSO performance
No systematic performance difference between chaotic and random sequences
Performance differences are due to underlying distribution, not sequence type
Abstract
Empirical results show that PSO performance may be different if using either chaotic or random sequences to drive the algorithm's search dynamics. We analyze the phenomenon by evaluating the performance based on a benchmark of test functions and comparing random and chaotic sequences according to equality or difference in underlying distribution or density. Our results show that the underlying distribution is the main influential factor in performance and thus the assumption of general and systematic performance differences between chaos and random appears not plausible.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsNeural Networks and Applications · Metaheuristic Optimization Algorithms Research · Complex Systems and Time Series Analysis
