Leveraging Dual Process Theory in Language Agent Framework for Real-time Simultaneous Human-AI Collaboration
Shao Zhang, Xihuai Wang, Wenhao Zhang, Chaoran Li, Junru Song, Tingyu Li, Lin Qiu, Xuezhi Cao, Xunliang Cai, Wen Yao, Weinan Zhang, Xinbing Wang, Ying Wen

TL;DR
This paper introduces DPT-Agent, a novel language agent framework that leverages Dual Process Theory to enable real-time, simultaneous human-AI collaboration, overcoming latency and inference challenges of existing models.
Contribution
The paper presents DPT-Agent, the first framework integrating System 1 and System 2 processes for autonomous, real-time human-AI collaboration using language models.
Findings
DPT-Agent significantly outperforms existing LLM frameworks in real-time tasks.
DPT-Agent effectively infers human intentions and makes autonomous decisions.
The framework demonstrates successful collaboration with both rule-based agents and humans.
Abstract
Agents built on large language models (LLMs) have excelled in turn-by-turn human-AI collaboration but struggle with simultaneous tasks requiring real-time interaction. Latency issues and the challenge of inferring variable human strategies hinder their ability to make autonomous decisions without explicit instructions. Through experiments with current independent System 1 and System 2 methods, we validate the necessity of using Dual Process Theory (DPT) in real-time tasks. We propose DPT-Agent, a novel language agent framework that integrates System 1 and System 2 for efficient real-time simultaneous human-AI collaboration. DPT-Agent's System 1 uses a Finite-state Machine (FSM) and code-as-policy for fast, intuitive, and controllable decision-making. DPT-Agent's System 2 integrates Theory of Mind (ToM) and asynchronous reflection to infer human intentions and perform reasoning-based…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
Taxonomy
TopicsRobotics and Automated Systems · Multi-Agent Systems and Negotiation · AI-based Problem Solving and Planning
