Graph Q-Learning for Combinatorial Optimization
Fuente:
arXiv
Saved in:
| Main Authors: | Dax, Victoria M., Li, Jiachen, Leahy, Kevin, Kochenderfer, Mykel J. |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Scaling Recurrent Neural Networks to a Billion Parameters with Zero-Order Optimization
by: Chaubard, Francois, et al.
Published: (2025)
by: Chaubard, Francois, et al.
Published: (2025)
Beyond Gradient Averaging in Parallel Optimization: Improved Robustness through Gradient Agreement Filtering
by: Chaubard, Francois, et al.
Published: (2024)
by: Chaubard, Francois, et al.
Published: (2024)
Multi-Agent Dynamic Relational Reasoning for Social Robot Navigation
by: Li, Jiachen, et al.
Published: (2024)
by: Li, Jiachen, et al.
Published: (2024)
Disentangled Neural Relational Inference for Interpretable Motion Prediction
by: Dax, Victoria M., et al.
Published: (2024)
by: Dax, Victoria M., et al.
Published: (2024)
Failure Probability Estimation for Black-Box Autonomous Systems using State-Dependent Importance Sampling Proposals
by: Delecki, Harrison, et al.
Published: (2024)
by: Delecki, Harrison, et al.
Published: (2024)
Zono-Conformal Prediction: Zonotope-Based Uncertainty Quantification for Regression and Classification Tasks
by: Lützow, Laura, et al.
Published: (2025)
by: Lützow, Laura, et al.
Published: (2025)
Imperfect World Models are Exploitable
by: Bhamidipaty, Logan Mondal, et al.
Published: (2026)
by: Bhamidipaty, Logan Mondal, et al.
Published: (2026)
BetterBench: Assessing AI Benchmarks, Uncovering Issues, and Establishing Best Practices
by: Reuel, Anka, et al.
Published: (2024)
by: Reuel, Anka, et al.
Published: (2024)
Combinatorial Optimization with Automated Graph Neural Networks
by: Liu, Yang, et al.
Published: (2024)
by: Liu, Yang, et al.
Published: (2024)
PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization
by: Hottung, André, et al.
Published: (2024)
by: Hottung, André, et al.
Published: (2024)
Enhanced Importance Sampling through Latent Space Exploration in Normalizing Flows
by: Kruse, Liam A., et al.
Published: (2025)
by: Kruse, Liam A., et al.
Published: (2025)
Decision-focused Graph Neural Networks for Combinatorial Optimization
by: Liu, Yang, et al.
Published: (2024)
by: Liu, Yang, et al.
Published: (2024)
Graph Reinforcement Learning for Combinatorial Optimization: A Survey and Unifying Perspective
by: Darvariu, Victor-Alexandru, et al.
Published: (2024)
by: Darvariu, Victor-Alexandru, et al.
Published: (2024)
Annealing Machine-assisted Learning of Graph Neural Network for Combinatorial Optimization
by: Loyola, Pablo, et al.
Published: (2025)
by: Loyola, Pablo, et al.
Published: (2025)
Permutation Picture of Graph Combinatorial Optimization Problems
by: Min, Yimeng
Published: (2024)
by: Min, Yimeng
Published: (2024)
Deep k-grouping: An Unsupervised Learning Framework for Combinatorial Optimization on Graphs and Hypergraphs
by: Bai, Sen, et al.
Published: (2025)
by: Bai, Sen, et al.
Published: (2025)
Scene Informer: Anchor-based Occlusion Inference and Trajectory Prediction in Partially Observable Environments
by: Lange, Bernard, et al.
Published: (2023)
by: Lange, Bernard, et al.
Published: (2023)
STRCMP: Integrating Graph Structural Priors with Language Models for Combinatorial Optimization
by: Li, Xijun, et al.
Published: (2025)
by: Li, Xijun, et al.
Published: (2025)
Bridging Visualization and Optimization: Multimodal Large Language Models on Graph-Structured Combinatorial Optimization
by: Zhao, Jie, et al.
Published: (2025)
by: Zhao, Jie, et al.
Published: (2025)
Self-Improved Learning for Scalable Neural Combinatorial Optimization
by: Luo, Fu, et al.
Published: (2024)
by: Luo, Fu, et al.
Published: (2024)
Divide and Learn: Multi-Objective Combinatorial Optimization at Scale
by: Singh, Esha, et al.
Published: (2026)
by: Singh, Esha, et al.
Published: (2026)
Structure As Search: Unsupervised Permutation Learning for Combinatorial Optimization
by: Min, Yimeng, et al.
Published: (2025)
by: Min, Yimeng, et al.
Published: (2025)
SCOUT: A Lightweight Framework for Scenario Coverage Assessment in Autonomous Driving
by: Yildiz, Anil, et al.
Published: (2025)
by: Yildiz, Anil, et al.
Published: (2025)
RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization Benchmark
by: Berto, Federico, et al.
Published: (2023)
by: Berto, Federico, et al.
Published: (2023)
Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning
by: Feng, Xinsong, et al.
Published: (2025)
by: Feng, Xinsong, et al.
Published: (2025)
Accelerating Proximal Policy Optimization Learning Using Task Prediction for Solving Environments with Delayed Rewards
by: Ahmad, Ahmad, et al.
Published: (2024)
by: Ahmad, Ahmad, et al.
Published: (2024)
Probing Neural Combinatorial Optimization Models
by: Zhang, Zhiqin, et al.
Published: (2025)
by: Zhang, Zhiqin, et al.
Published: (2025)
Transform then Explore: a Simple and Effective Technique for Exploratory Combinatorial Optimization with Reinforcement Learning
by: Pu, Tianle, et al.
Published: (2024)
by: Pu, Tianle, et al.
Published: (2024)
Deep Sensitivity Analysis for Objective-Oriented Combinatorial Optimization
by: Gireesan, Ganga, et al.
Published: (2024)
by: Gireesan, Ganga, et al.
Published: (2024)
Optimizing Falsification for Learning-Based Control Systems: A Multi-Fidelity Bayesian Approach
by: Shahrooei, Zahra, et al.
Published: (2024)
by: Shahrooei, Zahra, et al.
Published: (2024)
Learning to Solve Combinatorial Optimization under Positive Linear Constraints via Non-Autoregressive Neural Networks
by: Wang, Runzhong, et al.
Published: (2024)
by: Wang, Runzhong, et al.
Published: (2024)
Geometric Algorithms for Neural Combinatorial Optimization with Constraints
by: Karalias, Nikolaos, et al.
Published: (2025)
by: Karalias, Nikolaos, et al.
Published: (2025)
Binarizing Physics-Inspired GNNs for Combinatorial Optimization
by: Krutský, Martin, et al.
Published: (2025)
by: Krutský, Martin, et al.
Published: (2025)
Importance Sampling-Guided Meta-Training for Intelligent Agents in Highly Interactive Environments
by: Arief, Mansur, et al.
Published: (2024)
by: Arief, Mansur, et al.
Published: (2024)
Preference Elicitation for Multi-objective Combinatorial Optimization with Active Learning and Maximum Likelihood Estimation
by: Defresne, Marianne, et al.
Published: (2025)
by: Defresne, Marianne, et al.
Published: (2025)
Context-aware Diversity Enhancement for Neural Multi-Objective Combinatorial Optimization
by: Lu, Yongfan, et al.
Published: (2024)
by: Lu, Yongfan, et al.
Published: (2024)
A Combinatorial Theory of Dropout: Subnetworks, Graph Geometry, and Generalization
by: Dhayalkar, Sahil Rajesh
Published: (2025)
by: Dhayalkar, Sahil Rajesh
Published: (2025)
The Synergy Between Optimal Transport Theory and Multi-Agent Reinforcement Learning
by: Baheri, Ali, et al.
Published: (2024)
by: Baheri, Ali, et al.
Published: (2024)
Flow Q-Learning
by: Park, Seohong, et al.
Published: (2025)
by: Park, Seohong, et al.
Published: (2025)
CCMamba: Topologically-Informed Selective State-Space Networks on Combinatorial Complexes for Higher-Order Graph Learning
by: Chen, Jiawen, et al.
Published: (2026)
by: Chen, Jiawen, et al.
Published: (2026)
Similar Items
-
Scaling Recurrent Neural Networks to a Billion Parameters with Zero-Order Optimization
by: Chaubard, Francois, et al.
Published: (2025) -
Beyond Gradient Averaging in Parallel Optimization: Improved Robustness through Gradient Agreement Filtering
by: Chaubard, Francois, et al.
Published: (2024) -
Multi-Agent Dynamic Relational Reasoning for Social Robot Navigation
by: Li, Jiachen, et al.
Published: (2024) -
Disentangled Neural Relational Inference for Interpretable Motion Prediction
by: Dax, Victoria M., et al.
Published: (2024) -
Failure Probability Estimation for Black-Box Autonomous Systems using State-Dependent Importance Sampling Proposals
by: Delecki, Harrison, et al.
Published: (2024)