AI That Plans in Plain English
What if AI made plans in plain English before acting? This research shows that giving an agent a language “brainstorm” step can make it smarter and more reliable.
Instead of choosing thousands of tiny moves directly, the system first writes a short plan in natural language, then a second model executes it. The team built a tough real-time strategy game where many units must be coordinated over long periods. From 76,000 human play examples of instructions paired with actions, they trained an “instructor” and an “executor.”
Agents that use language as a hidden plan beat those that just imitate human clicks. The compositional structure of language—breaking big goals into smaller steps—was key to better decisions.
Why it matters: clearer, more controllable decisions; easier transfer to new tasks; and a path to human–AI collaboration. Code, models, and data are available. Read more: http://arxiv.org/abs/1906.00744v5
Paper: http://arxiv.org/abs/1906.00744v5
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#AI #NLP #ReinforcementLearning #HierarchicalRL #GameAI #MachineLearning #HumanAIInteraction
