MGA: Memory-Driven GUI Agent for Observation-Centric Interaction
Multimodal Large Language Models (MLLMs) have significantly advanced GUI agents, yet long-horizon automation remains constrained by two critical bottlenecks: context overload from raw sequential trajectory dependence and architectural redundancy from over-engineered expert modules.
Prevailing End-to-End and Multi-Agent paradigms struggle with error cascades caused by concatenated visual-textual histories and incur high inference latency due to redundant expert components, limiting their practical deployment. To address these issues, we propose the Memory-Driven GUI Agent (MGA), a minimalist framework that decouples long-horizon trajectories into independent decision steps linked by a structured state memory.
Key Features of MGA
MGA operates on an “Observe First and Memory Enhancement” principle, powered by two tightly coupled core mechanisms:
- Observer Module: Acts as a task-agnostic, intent-free screen state reader to eliminate confirmation bias, visual hallucinations, and perception bias at the root.
- Structured Memory Mechanism: Distills, validates, and compresses each interaction step into verified state deltas, constructing a lightweight state transition chain to avoid irrelevant historical interference and system redundancy.
Advantages of Using MGA
By replacing raw historical aggregation with compact, fact-based memory transitions, MGA drastically reduces cognitive overhead and system complexity. The simplification of the decision-making process allows for improved performance and efficiency in GUI tasks.
Experimental Validation
Extensive experiments on OSWorld and real-world applications demonstrate that MGA achieves highly competitive performance in open-ended GUI tasks while maintaining architectural simplicity. This innovative approach provides a scalable and efficient blueprint for next-generation GUI automation.
Conclusion
The Memory-Driven GUI Agent represents a significant step forward in the development of intelligent automation tools. By tackling the key challenges of context overload and architectural redundancy, MGA sets a new standard for GUI agents, paving the way for more effective and reliable automation solutions in various applications.
Further Information
For more details, visit the project’s GitHub page: MGA4OSWorld.