Towards Autonomous Agents: Adaptive-planning, Reasoning, and Acting in Language Models
<|reference_start|>Towards Autonomous Agents: Adaptive-planning, Reasoning, and Acting in Language Models: We propose a novel in-context learning algorithm for building autonomous decision-making language agents. The language agent continuously attempts to solve the same task by self-correcting each time the task fails. Our selected language agent demonstrates the ability to solve tasks in a text-based game environment. Our results show that the gemma-2-9b-it language model, using our proposed method, can successfully complete two of six tasks that failed in the first attempt. This highlights the effectiveness of our approach in enhancing the problem-solving capabilities of a single language model through self-correction, paving the way for more advanced autonomous agents. The code is publicly available at https://github.com/YenCheHsiao/AutonomousLLMAgentwithAdaptingPlanning.<|reference_end|>
@article{dutta2024towards,
    title={Towards Autonomous Agents: Adaptive-planning, Reasoning, and Acting in
  Language Models},
    author={Abhishek Dutta and Yen-Che Hsiao},
    journal={arXiv preprint arXiv:2408.06458},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.06458},
    primaryClass={cs.AI cs.CL}
}