3 papers
cs.AI2026
Hierarchical Reinforcement Learning in StarCraft Micromanagement with Influence Maps and Cluster-based Scripts
Chunhui Bai, Changhe Li, Dequan Li +2
Real-time strategy (RTS) games present significant AI challenges, characterized by expansive state-action spaces arising from multi-unit coordination in continuous battlefields, an…
cs.AI2026
SAT-RTS: A systematic framework for tactical knowledge extraction and visualization-based analysis in real-time strategy games
Chunhui Bai, Changhe Li, Yuqiang Li +2
Efficient tactical knowledge extraction and analysis in real-time strategy (RTS) games micromanagement are constrained by the high-dimensional coupled state-action sequential data…
cs.AI2025
Nearest-Better Network for Visualizing and Analyzing Combinatorial Optimization Problems: A Unified Tool
Yiya Diao, Changhe Li, Sanyou Zeng +4
The Nearest-Better Network (NBN) is a powerful method to visualize sampled data for continuous optimization problems while preserving multiple landscape features. However, the calc…