Metacognition is all you need? Using Introspection in Generative Agents
to Improve Goal-directed Behavior
- URL: http://arxiv.org/abs/2401.10910v2
- Date: Thu, 29 Feb 2024 21:05:00 GMT
- Title: Metacognition is all you need? Using Introspection in Generative Agents
to Improve Goal-directed Behavior
- Authors: Jason Toy, Josh MacAdam, Phil Tabor
- Abstract summary: We introduce a metacognition module for generative agents, enabling them to observe their own thought processes and actions.
We tested the metacognition module on a variety of scenarios, including a situation where generative agents must survive a zombie apocalypse.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Recent advances in Large Language Models (LLMs) have shown impressive
capabilities in various applications, yet LLMs face challenges such as limited
context windows and difficulties in generalization. In this paper, we introduce
a metacognition module for generative agents, enabling them to observe their
own thought processes and actions. This metacognitive approach, designed to
emulate System 1 and System 2 cognitive processes, allows agents to
significantly enhance their performance by modifying their strategy. We tested
the metacognition module on a variety of scenarios, including a situation where
generative agents must survive a zombie apocalypse, and observe that our system
outperform others, while agents adapt and improve their strategies to complete
tasks over time.
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