PC Agent is an AI system developed by GAIR-NLP that facilitates the creation of autonomous digital agents by transferring human cognitive processes. It comprises three key components: PC Tracker, a lightweight infrastructure for collecting large-scale human-computer interaction data; a Cognition Completion post-processing pipeline that converts raw interaction data into cognitive trajectories; and a multi-agent system combining a planning agent for decision-making with a grounding agent for robust visual grounding. PC Agent aims to enable AI to perform complex digital tasks autonomously by learning from human interactions.
Developing AI agents capable of autonomously performing complex digital tasks.
Collecting and utilizing human-computer interaction data for AI training.
Implementing multi-agent systems for decision-making and visual grounding.
Enhancing AI systems with human-like cognitive process understanding.
PC Agent demonstrates high-level autonomy through its ability to handle multi-step workflows (up to 50 steps) across applications without human intervention, using a cognitive architecture combining planning and grounding agents. It achieves Level 4 (Autonomous Goal-Driven) autonomy per the 5-level framework , showing strategic decision-making and task prioritization. However, limitations in handling novel situations and dependency on pre-collected cognitive trajectories prevent full autonomy. The system's two-stage cognition completion pipeline and human-like task decomposition capabilities enable sophisticated automation while requiring minimal supervision after initial setup.
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