A Note on Reinforcement Learning to Develop Self-defined Agents' Behavior

The document is an arXiv feed containing research on reinforcement-learning agents, temporal graph learning, agentic self-reflection, psychological network models, and attacks and defenses against multi-agent collaborative filtering systems. The security-relevant item studies dissemination and extraction attacks against autonomous LLM-based recommendation agents, including how system connectivity affects attack efficacy and defenses. No real-world incident, exploit, malware, or product-specific vulnerability is reported.