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Combinatorial optimization problems often rely on heuristic algorithms to generate efficient solutions. However, the manual design of heuristics is resource-intensive and constrained by the designer's expertise. Recent advances in…

Artificial Intelligence · Computer Science 2025-03-06 Thomas Bömer , Nico Koltermann , Max Disselnmeyer , Laura Dörr , Anne Meyer

This paper introduces a newly developed private key cryptosystem and a public key cryptosystem. In the first one, each letter is encrypted with a different key. Therefore, it is a kind of a one-time pad. The second one is inspired by the…

Group Theory · Mathematics 2016-03-09 Anja I. S. Moldenhauer , Gerhard Rosenberger

We consider a generalization of group testing where the potentially contaminated sets are the members of a given hypergraph ${\cal F}=(V,E)$. This generalization finds application in contexts where contaminations can be conditioned by some…

Data Structures and Algorithms · Computer Science 2023-11-28 Annalisa De Bonis

This paper proposes a generalized Hybrid Real-coded Quantum Evolutionary Algorithm (HRCQEA) for optimizing complex functions as well as combinatorial optimization. The main idea of HRCQEA is to devise a new technique for mutation and…

Neural and Evolutionary Computing · Computer Science 2013-03-07 Md. Amjad Hossain , Md. Kawser Hossain , M. M. A. Hashem

The growth of evolutionary computing (EC) methods in the exploration of complex potential energy landscapes of atomic and molecular clusters, as well as crystals over the last decade or so is reviewed. The trend of growth indicates that…

Materials Science · Physics 2015-09-02 Kanchan Sarkar , S. P. Bhattacharyya

Advanced Encryption Standard (AES) algorithm is considered as a secured algorithm. Still, some security issues lie in the S-Box and the key used. In this paper, we have tried to give focus on the security of the key used. Here, the proposed…

Cryptography and Security · Computer Science 2013-07-12 Chittaranjan Pradhan , Ajay Kumar Bisoi

Designing optimization approaches, whether heuristic or meta-heuristic, usually demands extensive manual intervention and has difficulty generalizing across diverse problem domains. The combination of Large Language Models (LLMs) and…

Neural and Evolutionary Computing · Computer Science 2024-10-29 He Yu , Jing Liu

It has been widely recognized that the performance of a multi-agent system is highly affected by its organization. A large scale system may have billions of possible ways of organization, which makes it impractical to find an optimal choice…

Multiagent Systems · Computer Science 2014-11-25 Zhiqi Shen , Ling Yu , Han Yu

Community detection, aiming to group nodes based on their connections, plays an important role in network analysis, since communities, treated as meta-nodes, allow us to create a large-scale map of a network to simplify its analysis.…

Social and Information Networks · Computer Science 2021-02-09 Jinyin Chen , Yixian Chen , Lihong Chen , Minghao Zhao , Qi Xuan

Stochastic gradient descent is the most prevalent algorithm to train neural networks. However, other approaches such as evolutionary algorithms are also applicable to this task. Evolutionary algorithms bring unique trade-offs that are worth…

Neural and Evolutionary Computing · Computer Science 2018-06-27 Jonas Prellberg , Oliver Kramer

There are several public key establishment protocols as well as complete public key cryptosystems based on allegedly hard problems from combinatorial (semi)group theory known by now. Most of these problems are search problems, i.e., they…

Group Theory · Mathematics 2007-05-23 Vladimir Shpilrain , Gabriel Zapata

We are often interested in clustering objects that evolve over time and identifying solutions to the clustering problem for every time step. Evolutionary clustering provides insight into cluster evolution and temporal changes in cluster…

Machine Learning · Computer Science 2019-12-30 Natalia M. Arzeno , Haris Vikalo

We apply entropy agglomeration (EA), a recently introduced algorithm, to cluster the words of a literary text. EA is a greedy agglomerative procedure that minimizes projection entropy (PE), a function that can quantify the segmentedness of…

Computation and Language · Computer Science 2014-10-28 Işık Barış Fidaner , Ali Taylan Cemgil

Artificial Intelligence (AI) agents have evolved from passive predictive tools into active entities capable of autonomous decision-making and environmental interaction, driven by the reasoning capabilities of Large Language Models (LLMs).…

Cryptography and Security · Computer Science 2026-03-24 Xiaolei Zhang , Lu Zhou , Xiaogang Xu , Jiafei Wu , Tianyu Du , Heqing Huang , Hao Peng , Zhe Liu

We propose a method of neural evolution structures (NESs) combining artificial neural networks (ANNs) and evolutionary algorithms (EAs) to generate High Entropy Alloys (HEAs) structures. Our inverse design approach is based on pair…

Disordered Systems and Neural Networks · Physics 2021-07-26 Conrard Giresse Tetsassi Feugmo , Kevin Ryczko , Abu Anand , Chandra Veer Singh , Isaac Tamblyn

The theory of finite simple groups is a (rather unexplored) area likely to provide interesting computational problems and modelling tools useful in a cryptographic context. In this note, we review some applications of finite non-abelian…

Group Theory · Mathematics 2023-08-29 María Isabel González Vasco , Delaram Kahrobaei , Eilidh McKemmie

Multiple Artificial Intelligence (AI) methods have been proposed over recent years to create controllers to play multiple video games of different nature and complexity without revealing the specific mechanics of each of these games to the…

Neural and Evolutionary Computing · Computer Science 2020-09-01 Edgar Galván , Oxana Gorshkova , Peter Mooney , Fred Valdez Ameneyro , Erik Cuevas

Cryptographic systems are derived using units in group rings. Combinations of types of units in group rings give units not of any particular type. This includes cases of taking powers of units and products of such powers and adds the…

Group Theory · Mathematics 2020-04-14 Barry Hurley , Ted Hurley

The hyperclimbing hypothesis is a hypothetical explanation for adaptation in genetic algorithms with uniform crossover (UGAs). Hyperclimbing is an intuitive, general-purpose, non-local search heuristic applicable to discrete product spaces…

Neural and Evolutionary Computing · Computer Science 2013-07-16 Keki M. Burjorjee

Homomorphic encryption (HE) is a promising cryptographic technique for enabling secure collaborative machine learning in the cloud. However, support for homomorphic computation on ciphertexts under multiple keys is inefficient. Current…

Cryptography and Security · Computer Science 2019-11-12 Asma Aloufi , Peizhao Hu