3 papers
cs.AI2026
Agent Alpha: Tree Search Unifying Generation, Exploration and Evaluation for Computer-Use Agents
Sizhe Tang, Rongqian Chen, Tian Lan
While scaling test-time compute through trajectory-level sampling has significantly improved Graphical User Interface (GUI) agents, the lack of regressive ability prevents the reus…
cs.LG2026
ACDZero: MCTS Agent for Mastering Automated Cyber Defense
Yu Li, Sizhe Tang, Rongqian Chen +5
Automated cyber defense (ACD) seeks to protect computer networks with minimal or no human intervention, reacting to intrusions by taking corrective actions such as isolating hosts,…
cs.AI2025
MALinZero: Efficient Low-Dimensional Search for Mastering Complex Multi-Agent Planning
Sizhe Tang, Jiayu Chen, Tian Lan
Monte Carlo Tree Search (MCTS), which leverages Upper Confidence Bound for Trees (UCTs) to balance exploration and exploitation through randomized sampling, is instrumental to solv…