Tag: AI Decision-Making
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LLM Reasoning Reveals Myopic Planning in Search Trees
Study uncovers shallow search depth and myopic planning in LLMs, highlighting key differences from human decision-making strategies.
When Do Language Models Commit? Finite-Answer Theory
Explore when language models commit to answers with finite-answer theory, revealing key insights into AI decision-making and response stabilization.
Theory of Agency in AI: Prediction & Empowerment via Interfaces
Explore a novel AI agency theory using bridge interfaces to enhance prediction, empowerment, and human-AI alignment in uncertain environments.
HiMAC: Hierarchical Learning for Long-Horizon LLM Agents
Discover HiMAC, a hierarchical learning framework boosting long-horizon planning and execution in LLM agents with improved efficiency and performance.
Contextual Multi-Objective Optimization in Frontier AI Systems
Explore how contextual multi-objective optimization improves AI decision-making by balancing complex, context-dependent goals in advanced frontier systems.