Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models

Some tasks — like planning problems — cannot be solved linearly. Chain-of-Thought works for step-by-step reasoning but fails when you need to explore multiple paths. Tree-of-Thoughts solves this but requires many separate LLM queries per problem plus external code to manage the tree. AoT’s insight is simpler: show the model examples of complete search trajectories — including backtracking and dead ends — and it learns to internalize the search itself. No external tree management. One query.