Navigating the Infinite Dynamic Web Space: Effective In-Context Exploration via Cognitive Multi-Agent Collaboration

AbstractDynamic web navigation is challenging due to infinite decision space and the constantly changing nature of cyberspace. Existing methods rely on greedy strategies or value estimation, struggle to achieve effective backtracking and are heavily dependent on proprietary models. In this paper, we propose HintNavigator, a cognitive multi-agent collaboration framework that enhances cyberspace exploration capability through In-Context Exploration (ICE). Inspired by the human cognitive planning process, we categorize the interaction history into Declarative History (environment observations) and Procedural History (action trajectories) to enhance historical reflection capability. These dual-history streams are dynamically integrated through specialized cognitive agents, enabling effective self-directed backtracking guided by working memory consolidation. Experiments show that HintNavigator achieves state-of-the-art performance among open-source LLM agents, surpassing proprietary model Claude-3.5 Sonnet on the WebArena benchmark.