Grounding the Agent: How Symbolic Rules Help LLMs Stay on Track

A College Project That Planted a Seed Years ago I was on a university team trying to build a Go AI. We explored monte carlo simulation for lookahead search, basic neural networks for pattern recognition, and expert systems for encoding domain knowledge. None of them worked well enough on their own. Go's branching factor is enormous, so brute-force search fails quickly. Neural networks without the right training data go nowhere. And even carefully written rules eventually hit a wall against a s...