Abstract: Spiking neural networks (SNNs) offer an effective approach to solving constraint satisfaction problems (CSPs) by leveraging their temporal, event-driven dynamics. Moreover, neuromorphic ...

2024, Paper: "This essay outlines foundations of the current moment facing corporations and politics, which I have characterized as a new “problem of twelve”—that is, the concentration of power in the ...

EasyCSP is an open-source Java library for Constraint Satisfaction Programming. Supports CSPs, CSOPs, discrete object domains, int interval domains, int constraint binarization. Examples include ...

Quadratically constrained quadratic programming (QCQP) problems appear in a wide range of engineering fields, including computer science, communication engineering, and finance. A key difficulty in ...

Aqarios' platform Luna v1.0 marks a major milestone in quantum optimization. This release significantly improves usability, performance, and real-world applicability by introducing FlexQAOA, a hybrid ...

1 School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China 2 School of Intelligent Systems and Engineering, Sun Yat-sen University, Shenzhen, China This study addresses the ...

Impact Statement: This work presents a novel approach to address Constraint Satisfaction Problems through Spiking Neural Networks (SNNs) utilising neuromorphic tools like the GeNN framework and the ...

Logical reasoning remains a crucial area where AI systems struggle despite advances in processing language and knowledge. Understanding logical reasoning in AI is essential for improving automated ...

An optaplanner planning problem related to satellites and tasks to assign to visibilities zones linked to that satellites. Used Quarkus and Constraint Streams. Tiny framework for solving constraint ...