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This chapter overviews a recently introduced network-based model of combinatorial landscapes: Local Optima Networks (LON). The model compresses the information given by the whole search space into a smaller mathematical object that is a…

Neural and Evolutionary Computing · Computer Science 2014-02-13 Gabriela Ochoa , Sébastien Verel , Fabio Daolio , Marco Tomassini

We propose a new way of looking at local optima networks (LONs). LONs represent fitness landscapes; the nodes are local optima, and the edges are search transitions between them. Many metrics computed on LONs have been proposed and shown to…

Neural and Evolutionary Computing · Computer Science 2024-01-18 Hendrik Richter , Sarah L. Thomson

Local Optima Networks (LONs) have been recently proposed as an alternative model of combinatorial fitness landscapes. The model compresses the information given by the whole search space into a smaller mathematical object that is the graph…

Artificial Intelligence · Computer Science 2012-10-16 Fabio Daolio , Sébastien Verel , Gabriela Ochoa , Marco Tomassini

Local Optima Networks (LONs) represent the global structure of search spaces as graphs, but their construction requires iterative execution of a search algorithm to find local optima and approximate transitions between Basins of Attraction…

Neural and Evolutionary Computing · Computer Science 2026-04-24 Kippei Mizuta , Shoichiro Tanaka , Shuhei Tanaka , Toshiharu Hatanaka

Local optima networks (LONs) capture fitness landscape information. They are typically constructed in a black-box manner; information about the problem structure is not utilised. This also applies to the analysis of LONs: knowledge about…

Neural and Evolutionary Computing · Computer Science 2025-04-28 S. L. Thomson , M. W. Przewozniczek

A Local Optima Network (LON) is a graph model that compresses the fitness landscape of a particular combinatorial optimization problem based on a specific neighborhood operator and a local search algorithm. Determining which and how…

Neural and Evolutionary Computing · Computer Science 2020-04-30 Marcella Scoczynski Ribeiro Martins , Mohamed El Yafrani , Myriam R. B. S. Delgado , Ricardo Luders

This study investigates the use of local optima network (LON) analysis, a derivative of the fitness landscape of candidate solutions, to characterise and visualise the neural architecture space. The search space of feedforward neural…

Neural and Evolutionary Computing · Computer Science 2022-06-15 Isak Potgieter , Christopher W. Cleghorn , Anna S. Bosman

Using a recently proposed model for combinatorial landscapes, Local Optima Networks (LON), we conduct a thorough analysis of two types of instances of the Quadratic Assignment Problem (QAP). This network model is a reduction of the…

Artificial Intelligence · Computer Science 2011-07-22 Fabio Daolio , Sébastien Verel , Gabriela Ochoa , Marco Tomassini

We introduce a model for the emergence of innovations, in which cognitive processes are described as random walks on the network of links among ideas or concepts, and an innovation corresponds to the first visit of a node. The transition…

Physics and Society · Physics 2018-01-25 Iacopo Iacopini , Staša Milojević , Vito Latora

Zipf's, Heaps' and Taylor's laws are ubiquitous in many different systems where innovation processes are at play. Together, they represent a compelling set of stylized facts regarding the overall statistics, the innovation rate and the…

Physics and Society · Physics 2018-11-14 Francesca Tria , Vittorio Loreto , Vito D. P. Servedio

Network-based representations of fitness landscapes have grown in popularity in the past decade; this is probably because of growing interest in explainability for optimisation algorithms. Local optima networks (LONs) have been especially…

Neural and Evolutionary Computing · Computer Science 2024-12-23 Sarah L. Thomson , Quentin Renau , Diederick Vermetten , Emma Hart , Niki van Stein , Anna V. Kononova

Morpho-evolution (ME) refers to the simultaneous optimisation of a robot's design and controller to maximise performance given a task and environment. Many genetic encodings have been proposed which are capable of representing design and…

Artificial Intelligence · Computer Science 2024-02-13 Sarah L. Thomson , Léni K. Le Goff , Emma Hart , Edgar Buchanan

We present Locally Orderless Networks (LON) and its theoretic foundation which links it to Convolutional Neural Networks (CNN), to Scale-space histograms, and measurement theory. The key elements are a regular sampling of the bias and the…

Computer Vision and Pattern Recognition · Computer Science 2024-06-21 Jon Sporring , Peidi Xu , Jiahao Lu , François Lauze , Sune Darkner

The notion of the "adjacent possible" has been advanced to theorize the generation of novelty across many different research domains. This study is an attempt to examine in what way the notion can be made empirically useful for innovation…

General Economics · Economics 2025-08-28 Josef Taalbi

Proximity networks are time-varying graphs representing the closeness among humans moving in a physical space. Their properties have been extensively studied in the past decade as they critically affect the behavior of spreading phenomena…

Physics and Society · Physics 2019-11-28 Fragkiskos Papadopoulos , Marco Antonio Rodríguez Flores

As a classical problem in the field of complex networks, link prediction has attracted much attention from researchers, which is of great significance to help us understand the evolution and dynamic development mechanisms of networks.…

Physics and Society · Physics 2022-06-07 Jiating Yu , Ling-Yun Wu

We develop a new framework for modeling innovation networks which evolve over time. The nodes in the network represent firms, whereas the directed links represent unilateral interactions between the firms. Both nodes and links evolve…

Physics and Society · Physics 2007-12-18 Michael D. Koenig , Stefano Battiston , Frank Schweitzer

We present a deterministic model for on-line social networks (OSNs) based on transitivity and local knowledge in social interactions. In the Iterated Local Transitivity (ILT) model, at each time-step and for every existing node $x$, a new…

Social and Information Networks · Computer Science 2013-08-16 Anthony Bonato , Noor Hadi , Paul Horn , Pawel Pralat , Changping Wang

Complex systems of many interacting components exhibit patterns of recurrence and emergent behaviors in their time evolution that can be understood from a new perspective of physics of information dynamics, modeled after one such system,…

Disordered Systems and Neural Networks · Physics 2026-01-27 Uday S. Goteti , Shane A. Cybart , Robert C. Dynes

Recent developments in fitness landscape analysis include the study of Local Optima Networks (LON) and applications of the Elementary Landscapes theory. This paper represents a first step at combining these two tools to explore their…

Artificial Intelligence · Computer Science 2012-10-16 Francisco Chicano , Fabio Daolio , Gabriela Ochoa , Sébastien Verel , Marco Tomassini , Enrique Alba
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