Artificial intelligence explores new ideas by tapping human intuition, a step toward humanlike intelligence.
Human know-how derives in part from our nose for novelty — we’re curious creatures, whether looking around corners or testing scientific hypotheses. For artificial intelligence to have a broad and nuanced understanding of the world — so it can navigate everyday obstacles, interact with strangers or invent new medicines — it also needs to explore new ideas and experiences on its own.
The researchers tested Intelligent Go-Explore, or IGE, on three types of tasks that require multistep solutions and involve processing and outputting text. In one, the system must arrange numbers and arithmetic operations to produce the number 24. In another, it completes tasks in a 2-D grid world, such as moving objects, based on text descriptions and instructions. In a third, it plays solo games that involve cooking, treasure hunting or collecting coins in a maze, also based on text.
OMNI-EPIC picks one task and uses LLMs to create a description and code for a new variation, then another LLM to decide if the new task is “interesting” . If it’s interesting, the AI agent trains on the task through reinforcement learning, and the task is saved into the archive, along with the newly trained agent and whether it was successful. The process repeats, creating a branching tree of new and more complex tasks along with AI agents that can complete them.
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