Multi-Agent Reinforcement Learning and Human Social Factors in Climate Change Mitigation. - Kyle Tilbury; Jesse Hoey (CoRR, 2020)

The Human Effect Requires Affect: Addressing Social-Psychological Factors of Climate Change with Machine Learning. - Kyle Tilbury; Jesse Hoey (CoRR, 2020)

Caring about Sharing: User Perceptions of Multiparty Data Sharing. - Bailey Kacsmar; Kyle Tilbury; Miti Mazmudar; Florian Kerschbaum (USENIX Security Symposium, 2022)

Identity and Dynamic Teams in Social Dilemmas. - Kyle Tilbury; Jesse Hoey (CoRR, 2022)

Comprehension from Chaos: What Users Understand and Expect from Private Computation. - Bailey Kacsmar; Vasisht Duddu; Kyle Tilbury; Blase Ur; Florian Kerschbaum (CoRR, 2022)

Comprehension from Chaos: Towards Informed Consent for Private Computation. - Bailey Kacsmar; Vasisht Duddu; Kyle Tilbury; Blase Ur; Florian Kerschbaum (CCS, 2023)

Towards a Better Understanding of Learning with Multiagent Teams. - David Radke; Kate Larson; Tim Brecht; Kyle Tilbury (IJCAI, 2023)

Learning to Learn Group Alignment: A Self-Tuning Credo Framework with Multiagent Teams. - David Radke; Kyle Tilbury (CoRR, 2023)

Simulating Tracking Data to Advance Sports Analytics Research. - David Radke; Kyle Tilbury (AAMAS, 2025)

Dynamic Reward Sharing to Enhance Learning in the Context of Multiagent Teams. - Kyle Tilbury; David Radke (AAMAS, 2025)