Publications
2024
Ryan Grant, Adam Goodie, Prashant Doshi, "The Human-Machine Teammate Inventory (HMTI): Scale Development and Validation", in PsyArXiv [Paper]
2024
Aditya Shinde, Prashant Doshi, "Modeling Cognitive Biases in Decision-Theoretic Planning for Active Cyber Deception", in AAMAS Conference [Paper]
2023
Keyang He, Prashant Doshi, Bikramjit Banerjee, "Modeling and Reinforcement Learning in Partially Observable Many-Agent Systems", in Journal of Autonomous Agents and Multi-Agent Systems [Article]
2023
Ehsan Asali, Prashant Doshi, Jin Sun, "Multi-View State-Action Recognition for Robust and Deployable Trajectory Generation", in Workshop on Reliable and Deployable Learning Based Robotic Systems, CoRL [Paper] [Presentation]
2023
Adam Eck, Leen-Kiat Soh, Prashant Doshi, "Decision Making in Open Agent Systems", in AI Magazine [Paper] [Presentation]
2023
Hannah Tawashy, Prashant Doshi, "Recurrent Sum-Product-Max Networks for Multi-Agent Decision Making: A Perspective", in MSDM 2023: 11th Workshop on Multi-Agent Sequential Decision-Making Under Uncertainty (MSDM), AAMAS [Paper] [Presentation]
2023
Prasanth Sengadu Suresh, Yikang Gui, Prashant Doshi, "Dec-AIRL: Decentralized Adversarial IRL for Human-Robot Teaming", in Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS) [Paper] [Presentation]
2023
Keyang He, Prashant Doshi, Bikramjit Banerjee, "Latent Interactive A2C for Improved RL in Open Many-Agent Systems", in arXiv:2305.05159 [Paper]
2022
Saurabh Arora, Bikramjit Banerjee, Prashant Doshi, "Online Inverse Reinforcement Learning with Learned Observation Model", in Conference on Robot Learning (CoRL) [Paper] [Supplement]
2022
Swaraj Pawar, Prashant Doshi, "Anytime Learning of Sum-Product and Sum-Product-Max Networks", in International Conference on Probabilistic Graphical Models (PGM) [Paper] [Supplement] [Presentation]
2022
Anirudh Kakarlapudi, Gayathri Anil, Adam Eck, Prashant Doshi, Leen-Kiat Soh, "Decision-Theoretic Planning with Communication in Open Multiagent Systems", in Conference on Uncertainty in AI (UAI) [Paper] [Supplement]
2022
Keyang He, Prashant Doshi, Bikramjit Banerjee, "Many-Agent Reinforcement Learning under Partial Observability", in Conference on Uncertainty in AI (UAI) [Paper] [Supplement]
2022
Prasanth Sengadu Suresh, Prashant Doshi, "Marginal MAP Estimation for Inverse RL under Occlusion with Observer Noise", in Conference on Uncertainty in AI (UAI) [Paper] [Supplement] [Presentation]
2022
Kenneth Bogert, Prashant Doshi, "A Hierarchical Bayesian Process for Inverse RL in Partially-Controlled Environments", in Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS) [Paper] [Supplement] [Presentation]
2022
Saurabh Steixner-Kumar, Tessa Rusch, Prashant Doshi, Michael Spezio, Jan Glascher, "Humans depart from optimal computational models of interactive decision‑making during competition under partial information", in Scientific Reports, Springer Nature, 2022 [Article]