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

This repository contains implementations of reinforcement learning approaches for stochastic constraint satisfaction problems. These are optimization problems where decisions must be made sequentially ...

Abstract: Over the last ten years, constraint logic programming (CLP) has evolved into a interesting research held. In this tutorial we show that CLP is now also an industrial reality with an ...

Timefold Solver is an AI constraint solver for Python to optimize the Vehicle Routing Problem, Employee Rostering, Maintenance Scheduling, Task Assignment, School Timetabling, Cloud Optimization, ...

Dung Le, a distinguished software engineer and entrepreneur, has built an impressive career spanning prestigious technology companies and venture-backed startups. He holds a  B.S. in Computer Science ...

Prateek Panigrahy is a senior data analytics leader based in Westlake, Texas, with over 16 years of experience in the Business Intelligence domain. With a solid educational foundation including a ...