Research paper proposing a bilevel optimization approach using Monte Carlo Tree Search to optimize AI agent skills. Combines hierarchical optimization with MCTS sampling to improve agent capability learning and adaptation.
Research
Bilevel Optimization of Agent Skills via Monte Carlo Tree Search
Bilevel optimization combined with Monte Carlo Tree Search enables more efficient hierarchical learning of AI agent capabilities through adaptive sampling.
Monday, April 20, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.AIBY sys://pipeline
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