# RL for games and combinatorial optimization

Area: [Deep reinforcement learning methods](https://mlsanity.com/deeprl/index.md). HTML: https://mlsanity.com/deeprl/rl-for-games-and-combinatorial-optimization/

## Key facts

- RL for games and combinatorial optimization: 560 papers on arXiv since 2024 (data through 14 Oct 2026).
- 6 of its 560 mapped papers (1%) cite “Bridging Evolutionary Algorithms and Reinforcement Learning: A Comprehensive Survey on Hybrid Algorithms” (2024, arXiv 2401.11963).
- 6 of its 560 mapped papers (1%) cite “When is Mean-Field Reinforcement Learning Tractable and Relevant?” (2024, arXiv 2402.05757).
- 9 new papers 30 Sep–14 Oct.

## Most cited here

- [Bridging Evolutionary Algorithms and Reinforcement Learning: A Comprehensive Survey on Hybrid Algorithms](https://mlsanity.com/paper/2401.11963/) (2024), cited by 6 papers here
- [When is Mean-Field Reinforcement Learning Tractable and Relevant?](https://mlsanity.com/paper/2402.05757/) (2024), cited by 6 papers here
- [Deep Reinforcement Learning for Dynamic Algorithm Selection: A Proof-of-Principle Study on Differential Evolution](https://mlsanity.com/paper/2403.02131/) (2024), cited by 6 papers here
- [Pareto Set Learning for Multi-Objective Reinforcement Learning](https://mlsanity.com/paper/2501.06773/) (2025), cited by 6 papers here
- [Reevaluating Policy Gradient Methods for Imperfect-Information Games](https://mlsanity.com/paper/2502.08938/) (2025), cited by 6 papers here
- [INViT: A Generalizable Routing Problem Solver with Invariant Nested View Transformer](https://mlsanity.com/paper/2402.02317/) (2024), cited by 5 papers here
- [Graph Reinforcement Learning for Combinatorial Optimization: A Survey and Unifying Perspective](https://mlsanity.com/paper/2404.06492/) (2024), cited by 5 papers here
- [Auto-configuring Exploration-Exploitation Tradeoff in Evolutionary Computation via Deep Reinforcement Learning](https://mlsanity.com/paper/2404.08239/) (2024), cited by 5 papers here
- [Sample Complexity of the Linear Quadratic Regulator: A Reinforcement Learning Lens](https://mlsanity.com/paper/2404.10851/) (2024), cited by 5 papers here
- [Full error analysis of policy gradient learning algorithms for exploratory linear quadratic mean-field control problem in continuous time with common noise](https://mlsanity.com/paper/2408.02489/) (2024), cited by 5 papers here

## New (30 Sep–14 Oct)

- [Learning to Play: Reinforcement Learning and Games](https://mlsanity.com/paper/2610.17391/) (2026-10-12)
- [Integrating AIRL-Based Reward Estimation into a Control Method Using Fuzzy Inference and Policy Gradient](https://mlsanity.com/paper/2610.14723/) (2026-10-10)
- [Toward Maximizing Algebraic Connectivity via Density-Dependent Backbone Construction and Reinforcement Learning Completion](https://mlsanity.com/paper/2610.12697/) (2026-10-08)
- [Can AI Agents Learn Their Way to the Top? Evaluating Heuristic Learning in a Long-Running Game Agent Competition](https://mlsanity.com/paper/2610.12341/) (2026-10-08)
- [Constrained Command-Conditioned Reinforcement Learning with Bandit Strategy Selection in Real-Time Strategy Games](https://mlsanity.com/paper/2610.11663/) (2026-10-08)
- [Self-Referenced Social Preferences: Cooperation without Observing Others Rewards](https://mlsanity.com/paper/2610.07881/) (2026-10-06)
- [Factoriax: A GPU-Accelerated Factorio-Style Simulator for Reinforcement Learning](https://mlsanity.com/paper/2610.05569/) (2026-10-04)
- [Mastering Atari 2600 Games with Discovered Options](https://mlsanity.com/paper/2610.03604/) (2026-10-02)
- [Reinforcement Learning to Accelerate Primal-Dual Hybrid Gradient for Linear Programming](https://mlsanity.com/paper/2610.01546/) (2026-10-01)