paper-with-me

Papers

Scale-invariance of ruggedness measures in fractal fitness landscapes

2016-12-21 · Hendrik Richter

The paper deals with using chaos to direct trajectories to targets and analyzes ruggedness and fractality of the resulting fitness landscapes. The targeting problem is formulated as a dynamic fitness landscape and four different chaotic maps generating such a landscape are studied. By using a computational approach, we analyze properties of the landscapes and quantify their fractal and rugged characteristics. In particular, it is shown that ruggedness measures such as correlation length and information content are scale-invariant and self-similar.

📄 PDF Abstract BibTeX arXiv:1612.07029

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Dynamic landscape models of coevolutionary games

2016-11-28 · Hendrik Richter

Players of coevolutionary games may update not only their strategies but also their networks of interaction. Based on interpreting the payoff of players as fitness, dynamic landscape models are proposed. The modeling pro…

A Study of Fitness Landscapes for Neuroevolution

2020-01-30 · Nuno M. Rodrigues, Sara Silva, Leonardo Vanneschi

Fitness landscapes are a useful concept to study the dynamics of meta-heuristics. In the last two decades, they have been applied with success to estimate the optimization power of several types of evolutionary algorithm…

Evolutionary Algorithms

FRACTAL: SSM with Fractional Recurrent Architecture for Computational Temporal Analysis of Long Sequences

2026-05-09 · Mengqi Li, Wensheng Lin, Jinshuai Yang, Lixin Li arxiv

Effective sequence modeling fundamentally requires balancing the retention of unbounded history with the high-resolution detection of abrupt short-term variations common in real-world phenomena. However, existing state s…

A Simple Haploid-Diploid Evolutionary Algorithm

2019-03-27 · Larry Bull

It has recently been suggested that evolution exploits a form of fitness landscape smoothing within eukaryotic sex due to the haploid-diploid cycle. This short paper presents a simple modification to the standard evoluti…

Recursive Self-Similarity in Deep Weight Spaces of Neural Architectures: A Fractal and Coarse Geometry Perspective

2025-03-18 · Ambarish Moharil, Indika Kumara, Damian Andrew Tamburri, Majid Mohammadi 외

This paper conceptualizes the Deep Weight Spaces (DWS) of neural architectures as hierarchical, fractal-like, coarse geometric structures observable at discrete integer scales through recursive dilation. We introduce a c…