TY - JOUR AU - Shepherd, Patrick AU - Goldsmith, Judy PY - 2020/04/03 Y2 - 2024/03/29 TI - A Reinforcement Learning Approach to Strategic Belief Revelation with Social Influence JF - Proceedings of the AAAI Conference on Artificial Intelligence JA - AAAI VL - 34 IS - 10 SE - Doctoral Consortium Track DO - 10.1609/aaai.v34i10.7139 UR - https://ojs.aaai.org/index.php/AAAI/article/view/7139 SP - 13734-13735 AB - <p>The study of social networks has increased rapidly in the past few decades. Of recent interest are the dynamics of changing opinions over a network. Some research has investigated how interpersonal influence can affect opinion change, how to maximize/minimize the spread of opinion change over a network, and recently, if/how agents can act strategically to effect some outcome in the network's opinion distribution. This latter problem can be modeled and addressed as a reinforcement learning problem; we introduce an approach to help network agents find strategies that outperform hand-crafted policies. Our preliminary results show that our approach is promising in networks with dynamic topologies.</p> ER -