GGBond is an agent-based simulator that couples a five-layer cognitive agent model with a dynamic multilayer social graph to evaluate recommender systems under long-term feedback.
Agentic feedback loop modeling improves recommendation and user simulation
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GGBond: Growing Graph-Based AI-Agent Society for Socially-Aware Recommender Simulation
GGBond is an agent-based simulator that couples a five-layer cognitive agent model with a dynamic multilayer social graph to evaluate recommender systems under long-term feedback.