Co-Evolving LLM Decision and Skill Bank Agents for Long-Horizon Tasks

1. 1Define a long-horizon task environment using a game or simulation framework
2. 2Implement a Large Language Model (LLM) as a decision-making agent
3. 3Create a skill bank to store and manage multiple skills for the agent
4. 4Co-evolve the LLM decision agent and skill bank using reinforcement learning or evolutionary algorithms
5. 5Test and evaluate the co-evolved agent in the long-horizon task environment

AI researchers and engineers working on long-horizon tasks, such as game playing or complex decision-making, can benefit from this approach to improve agent performance and robustness

💡 Co-evolving LLM decision and skill bank agents can improve agent performance and robustness in long-horizon tasks by enabling multi-step reasoning and skill chaining

🤖 Co-evolve LLM decision & skill bank agents for long-horizon tasks! 🚀 Improve multi-step reasoning & skill chaining in interactive environments #AI #LLMs #GamePlaying