activity
20192025
most citedA Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics Network

41 citations · 45 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI2025

Model-Based and Sample-Efficient AI-Assisted Math Discovery in Sphere Packing

Rasul Tutunov, Alexandre Maraval, Antoine Grosnit +3

Sphere packing, Hilbert's eighteenth problem, asks for the densest arrangement of congruent spheres in n-dimensional Euclidean space. Although relevant to areas such as cryptograph…

cs.LO2024

Logic Synthesis with Generative Deep Neural Networks

Xihan Li, Xing Li, Lei Chen +3

While deep learning has achieved significant success in various domains, its application to logic circuit design has been limited due to complex constraints and strict feasibility…

cs.LG2024★ 1 cited

Circuit Transformer: A Transformer That Preserves Logical Equivalence

Xihan Li, Xing Li, Lei Chen +3

Implementing Boolean functions with circuits consisting of logic gates is fundamental in digital computer design. However, the implemented circuit must be exactly equivalent, which…

quant-ph2022

Self-consistent Gradient-like Eigen Decomposition in Solving Schrödinger Equations

Xihan Li, Xiang Chen, Rasul Tutunov +3

The Schrödinger equation is at the heart of modern quantum mechanics. Since exact solutions of the ground state are typically intractable, standard approaches approximate Schröding…

cs.MS2021★ 3 cited

Grassland: A Rapid Algebraic Modeling System for Million-variable Optimization

Xihan Li, Xiongwei Han, Zhishuo Zhou +3

An algebraic modeling system (AMS) is a type of mathematical software for optimization problems, which allows users to define symbolic mathematical models in a specific language, i…

cs.MA2019★ 41 cited

A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics Network

Xihan Li, Jia Zhang, Jiang Bian +2

Resource balancing within complex transportation networks is one of the most important problems in real logistics domain. Traditional solutions on these problems leverage combinato…