Prashant Doshi

ORCID

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 69

Top Venues

Publications

Aditya Shinde, Prashant Doshi
Modeling Cognitive Biases in Decision-theoretic Planning for Active Cyber Deception. AAMAS (2024)
Keyang He, Prashant Doshi, Bikramjit Banerjee
Modeling and reinforcement learning in partially observable many-agent systems. Auton. Agents Multi Agent Syst. 38 (1) (2024)
Adam Eck, Leen-Kiat Soh, Prashant Doshi
Decision making in open agent systems. AI Mag. 44 (4) (2023)
Keyang He, Prashant Doshi, Bikramjit Banerjee
Latent Interactive A2C for Improved RL in Open Many-Agent Systems. CoRR (2023)
Yikang Gui, Prashant Doshi
A Novel Variational Lower Bound for Inverse Reinforcement Learning. CoRR (2023)
Ehsan Asali, Prashant Doshi, Jin Sun
MVSA-Net: Multi-View State-Action Recognition for Robust and Deployable Trajectory Generation. CoRR (2023)
Prasanth Sengadu Suresh, Yikang Gui, Prashant Doshi
Dec-AIRL: Decentralized Adversarial IRL for Human-Robot Teaming. AAMAS (2023)
Anirudh Kakarlapudi, Gayathri Anil, Adam Eck, Prashant Doshi, Leen-Kiat Soh
Decision-theoretic planning with communication in open multiagent systems. UAI (2022)
Gengyu Zhang, Prashant Doshi
SIPOMDPLite-Net: Lightweight, Self-Interested Learning and Planning in POSGs with Sparse Interactions. CoRR (2022)
Kenneth D. Bogert, Prashant Doshi
A Hierarchical Bayesian Process for Inverse RL in Partially-Controlled Environments. AAMAS (2022)
Kenneth D. Bogert, Yikang Gui, Prashant Doshi
IRL with Partial Observations using the Principle of Uncertain Maximum Entropy. CoRR (2022)
Swaraj Pawar, Prashant Doshi
Anytime Learning of Sum-Product and Sum-Product-Max Networks. PGM (2022)
Saurabh Arora, Prashant Doshi, Bikramjit Banerjee
Online Inverse Reinforcement Learning with Learned Observation Model. CoRL (2022)
Keyang He, Prashant Doshi, Bikramjit Banerjee
Reinforcement learning in many-agent settings under partial observability. UAI (2022)
Prasanth Sengadu Suresh, Prashant Doshi
Marginal MAP estimation for inverse RL under occlusion with observer noise. UAI (2022)
Roi Ceren, Keyang He, Prashant Doshi, Bikramjit Banerjee
PALO bounds for reinforcement learning in partially observable stochastic games. Neurocomputing 420 (2021)
Keyang He, Prashant Doshi, Bikramjit Banerjee
Many Agent Reinforcement Learning Under Partial Observability. CoRR (2021)
Prasanth Sengadu Suresh, Prashant Doshi
Marginal MAP Estimation for Inverse RL under Occlusion with Observer Noise. CoRR (2021)
Saurabh Arora, Prashant Doshi
A survey of inverse reinforcement learning: Challenges, methods and progress. Artif. Intell. 297 (2021)
Muhammed AbuOdeh, Christian Adkins, Omid Setayeshfar, Prashant Doshi, Kyu Hyung Lee
A Novel AI-based Methodology for Identifying Cyber Attacks in Honey Pots. AAAI (2021)
Keyang He, Bikramjit Banerjee, Prashant Doshi
Cooperative-Competitive Reinforcement Learning with History-Dependent Rewards. AAMAS (2021)
Aditya Shinde, Prashant Doshi, Omid Setayeshfar
Cyber Attack Intent Recognition and Active Deception using Factored Interactive POMDPs. AAMAS (2021)
Saurabh Arora, Prashant Doshi, Bikramjit Banerjee
Min-Max Entropy Inverse RL of Multiple Tasks. ICRA (2021)
Saurabh Arora, Prashant Doshi, Bikramjit Banerjee
I2RL: online inverse reinforcement learning under occlusion. Auton. Agents Multi Agent Syst. 35 (1) (2021)
Omid Setayeshfar, Christian Adkins, Matthew Jones, Kyu Hyung Lee, Prashant Doshi
GrAALF: Supporting graphical analysis of audit logs for forensics. Softw. Impacts 8 (2021)
Layton Hayes, Prashant Doshi, Swaraj Pawar, Hari Teja Tatavarti
State-Based Recurrent SPMNs for Decision-Theoretic Planning under Partial Observability. IJCAI (2021)
Kenneth D. Bogert, Prashant Doshi
A Hierarchical Bayesian model for Inverse RL in Partially-Controlled Environments. CoRR (2021)
Hari Teja Tatavarti, Prashant Doshi, Layton Hayes
Data-Driven Decision-Theoretic Planning using Recurrent Sum-Product-Max Networks. ICAPS (2021)
Aditya Shinde, Prashant Doshi, Omid Setayeshfar
Active Deception using Factored Interactive POMDPs to Recognize Cyber Attacker's Intent. CoRR (2020)
Keyang He, Bikramjit Banerjee, Prashant Doshi
Cooperative-Competitive Reinforcement Learning with History-Dependent Rewards. CoRR (2020)
Prashant Doshi, Piotr J. Gmytrasiewicz, Edmund H. Durfee
Recursively modeling other agents for decision making: A research perspective. Artif. Intell. 279 (2020)
Nihal Soans, Ehsan Asali, Yi Hong, Prashant Doshi
SA-Net: Robust State-Action Recognition for Learning from Observations. ICRA (2020)
Adam Eck, Maulik Shah, Prashant Doshi, Leen-Kiat Soh
Scalable Decision-Theoretic Planning in Open and Typed Multiagent Systems. AAAI (2020)
Saurabh Arora, Bikramjit Banerjee, Prashant Doshi
Maximum Entropy Multi-Task Inverse RL. CoRR (2020)
Hari Teja Tatavarti, Prashant Doshi, Layton Hayes
Recurrent Sum-Product-Max Networks for Decision Making in Perfectly-Observed Environments. CoRR (2020)
Omid Setayeshfar, Christian Adkins, Matthew Jones, Kyu Hyung Lee, Prashant Doshi
GrAALF: Supporting Graphical Analysis of Audit Logs for Forensics. CoRR (2019)
Tomoki Nishi, Prashant Doshi, Danil V. Prokhorov
Merging in Congested Freeway Traffic Using Multipolicy Decision Making and Passive Actor-Critic Learning. IEEE Trans. Intell. Veh. 4 (2) (2019)
Vinamra Jain, Prashant Doshi, Bikramjit Banerjee
Model-Free IRL Using Maximum Likelihood Estimation. AAAI (2019)
Saurabh Arora, Prashant Doshi, Bikramjit Banerjee
Online Inverse Reinforcement Learning Under Occlusion. AAMAS (2019)
Nihal Soans, Yi Hong, Prashant Doshi
SA-Net: Deep Neural Network for Robot Trajectory Recognition from RGB-D Streams. CoRR (2019)
Adam Eck, Maulik Shah, Prashant Doshi, Leen-Kiat Soh
Scalable Decision-Theoretic Planning in Open and Typed Multiagent Systems. CoRR (2019)
Adithya Raam Sankar, Prashant Doshi, Adam Goodie
Evacuate or Not? A POMDP Model of the Decision Making of Individuals in Hurricane Evacuation Zones. UAI (2019)
Agastya Kalra, Abdullah Rashwan, Wei-Shou Hsu, Pascal Poupart, Prashant Doshi, Georgios Trimponias
Online Structure Learning for Feed-Forward and Recurrent Sum-Product Networks. NeurIPS (2018)
Saurabh Arora, Prashant Doshi, Bikramjit Banerjee
A Framework and Method for Online Inverse Reinforcement Learning. CoRR (2018)
Maulesh Trivedi, Prashant Doshi
Inverse Learning of Robot Behavior for Collaborative Planning. IROS (2018)
Saurabh Arora, Prashant Doshi
A Survey of Inverse Reinforcement Learning: Challenges, Methods and Progress. CoRR (2018)
Roi Ceren, Prashant Doshi, Keyang He
Reinforcement Learning for Heterogeneous Teams with PALO Bounds. CoRR (2018)
Kenneth D. Bogert, Prashant Doshi
Multi-robot inverse reinforcement learning under occlusion with estimation of state transitions. Artif. Intell. 263 (2018)
Tomoki Nishi, Prashant Doshi, Michael R. James, Danil V. Prokhorov
Actor-Critic for Linearly-Solvable Continuous MDP with Partially Known Dynamics. CoRR (2017)
Tomoki Nishi, Prashant Doshi, Danil V. Prokhorov
Freeway Merging in Congested Traffic based on Multipolicy Decision Making with Passive Actor Critic. CoRR (2017)
Muthukumaran Chandrasekaran, Prashant Doshi, Yifeng Zeng, Yingke Chen
Can bounded and self-interested agents be teammates? Application to planning in ad hoc teams. Auton. Agents Multi Agent Syst. 31 (4) (2017)
Muthukumaran Chandrasekaran, Junhuan Zhang, Prashant Doshi, Yifeng Zeng
Robust Model Equivalence using Stochastic Bisimulation for N-Agent Interactive DIDs. UAI (2017)
Muthukumaran Chandrasekaran, Yingke Chen, Prashant Doshi
On Markov Games Played by Bayesian and Boundedly-Rational Players. AAAI (2017)
Xia Qu, Prashant Doshi
On the role of fairness and limited backward induction in sequential bargaining games - New behavioral models and analyses. Ann. Math. Artif. Intell. 79 (1-3) (2017)
Shervin Shahryari, Prashant Doshi
Inverse Reinforcement Learning Under Noisy Observations. CoRR (2017)
Shervin Shahryari, Prashant Doshi
Inverse Reinforcement Learning Under Noisy Observations. AAMAS (2017)
Sina Solaimanpour, Prashant Doshi
A layered HMM for predicting motion of a leader in multi-robot settings. ICRA (2017)
Kenneth D. Bogert, Prashant Doshi
Scaling Expectation-Maximization for Inverse Reinforcement Learning to Multiple Robots under Occlusion. AAMAS (2017)
Ekhlas Sonu, Yingke Chen, Prashant Doshi
Decision-Theoretic Planning Under Anonymity in Agent Populations. J. Artif. Intell. Res. 59 (2017)
Mazen Melibari, Pascal Poupart, Prashant Doshi, George Trimponias
Dynamic Sum Product Networks for Tractable Inference on Sequence Data. Probabilistic Graphical Models (2016)
Kenneth D. Bogert, Jonathan Feng-Shun Lin, Prashant Doshi, Dana Kulic
Expectation-Maximization for Inverse Reinforcement Learning with Hidden Data. AAMAS (2016)
Mazen A. Melibari, Pascal Poupart, Prashant Doshi
Sum-Product-Max Networks for Tractable Decision Making: (Extended Abstract). AAMAS (2016)
Mazen Melibari, Pascal Poupart, Prashant Doshi
Sum-Product-Max Networks for Tractable Decision Making. IJCAI (2016)
Muthukumaran Chandrasekaran, Yingke Chen, Prashant Doshi
Bayesian Markov Games with Explicit Finite-Level Types. AAAI Workshop: Multiagent Interaction without Prior Coordination (2016)
Roi Ceren, Prashant Doshi, Bikramjit Banerjee
Reinforcement Learning in Partially Observable Multiagent Settings: Monte Carlo Exploring Policies with PAC Bounds. AAMAS (2016)
Mazen Melibari, Pascal Poupart, Prashant Doshi
Decision Sum-Product-Max Networks. AAAI (2016)
Muthukumaran Chandrasekaran, Adam Eck, Prashant Doshi, Leenkiat Soh
Individual Planning in Open and Typed Agent Systems. UAI (2016)
Muthukumaran Chandrasekaran, Yingke Chen, Prashant Doshi
Bayesian Markov Games with Explicit Finite-Level Types. AAAI (2016)
Yifeng Zeng, Prashant Doshi, Yingke Chen, Yinghui Pan, Hua Mao, Muthukumaran Chandrasekaran
Approximating behavioral equivalence for scaling solutions of I-DIDs. Knowl. Inf. Syst. 49 (2) (2016)
Fadel Adoe, Yingke Chen, Prashant Doshi
Fast Solving of Influence Diagrams for Multiagent Planning on GPU-enabled Architectures. ICAART (2) (2015)
Amir H. Asiaee, Todd Minning, Prashant Doshi, Rick L. Tarleton
A framework for ontology-based question answering with application to parasite immunology. J. Biomed. Semant. 6 (2015)
Xia Qu, Prashant Doshi
Individual Planning in Infinite-Horizon Multiagent Settings: Inference, Structure and Scalability. NIPS (2015)
Kenneth D. Bogert, Prashant Doshi
Multi-Robot Inverse Reinforcement Learning Under Occlusion with State Transition Estimation. AAMAS (2015)
Mazen Melibari, Pascal Poupart, Prashant Doshi
Dynamic Sum Product Networks for Tractable Inference on Sequence Data. CoRR (2015)
Ekhlas Sonu, Yingke Chen, Prashant Doshi
Individual Planning in Agent Populations: Exploiting Anonymity and Frame-Action Hypergraphs. ICAPS (2015)
ChanMin Kim, Dongho Kim, Jiangmei Yuan, Roger B. Hill, Prashant Doshi, Chi N. Thai
Robotics to promote elementary education pre-service teachers' STEM engagement, learning, and teaching. Comput. Educ. 91 (2015)
Ekhlas Sonu, Yingke Chen, Prashant Doshi
Individual Planning in Agent Populations: Exploiting Anonymity and Frame-Action Hypergraphs. CoRR (2015)
Fadel Adoe, Yingke Chen, Prashant Doshi
Speeding up Planning in Multiagent Settings Using CPU-GPU Architectures. ICAART (Revised Selected Papers) (2015)
Kedar Marathe, Prashant Doshi
Localization and tracking under extreme and persistent sensory occlusion. IROS (2015)
Kenneth D. Bogert, Prashant Doshi
Toward Estimating Others' Transition Models Under Occlusion for Multi-Robot IRL. IJCAI (2015)
Kenneth D. Bogert, Sina Solaimanpour, Prashant Doshi
Aerial Robotic Simulations for Evaluation of Multi-Agent Planning in GaTAC. AAMAS (2015)
Xia Qu, Prashant Doshi
Improved Planning for Infinite-Horizon Interactive POMDPs using Probabilistic Inference (Extended Abstract). AAMAS (2015)
Yingke Chen, Prashant Doshi, Yifeng Zeng
Iterative Online Planning in Multiagent Settings with Limited Model Spaces and PAC Guarantees. AAMAS (2015)
Ekhlas Sonu, Prashant Doshi
Scalable solutions of interactive POMDPs using generalized and bounded policy iteration. Auton. Agents Multi Agent Syst. 29 (3) (2015)
Muthukumaran Chandrasekaran, Prashant Doshi, Yifeng Zeng, Yingke Chen
Team Behavior in Interactive Dynamic Influence Diagrams with Applications to Ad Hoc Teams. CoRR (2014)
ChanMin Kim, Prashant Doshi, Chi N. Thai, Dongho Kim, Jiangmei Yuan
A Portal Designed to Learn about Educational Robotics. CogSci (2014)
Muthukumaran Chandrasekaran, Prashant Doshi, Yifeng Zeng, Yingke Chen
Team behavior in interactive dynamic influence diagrams with applications to ad hoc teams. AAMAS (2014)
Uthayasanker Thayasivam, Prashant Doshi
Speeding Up Iterative Ontology Alignment using Block-Coordinate Descent. J. Artif. Intell. Res. 50 (2014)
Prashant Doshi, Piotr J. Gmytrasiewicz
Monte Carlo Sampling Methods for Approximating Interactive POMDPs. CoRR (2014)
Yifeng Zeng, Prashant Doshi
Exploiting Model Equivalences for Solving Interactive Dynamic Influence Diagrams. CoRR (2014)
Xia Qu, Prashant Doshi
Behavioral Modeling of Sequential Bargaining Games: Fairness and Limited Backward Induction. ISAIM (2014)
Kenneth D. Bogert, Prashant Doshi
Multi-robot inverse reinforcement learning under occlusion with interactions. AAMAS (2014)
Roi Ceren, Prashant Doshi, Matthew Meisel, Adam Goodie, Dan Hall
On Modeling Human Learning in Sequential Games with Delayed Reinforcements. SMC (2013)
Tejas Chaudhari, Uthayasanker Thayasivam, Prashant Doshi
Canonical Forms and Similarity of Complex Concepts for Improved Ontology Alignment. Web Intelligence (2013)
Amir H. Asiaee, Prashant Doshi, Todd Minning, Satya Sanket Sahoo, Priti Parikh, Amit P. Sheth, Rick L. Tarleton
From Questions to Effective Answers: On the Utility of Knowledge-Driven Querying Systems for Life Sciences Data. DILS (2013)
Ekhlas Sonu, Prashant Doshi
Bimodal Switching for Online Planning in Multiagent Settings. IJCAI (2013)
Uthayasanker Thayasivam, Prashant Doshi
Speeding Up Batch Alignment of Large Ontologies Using MapReduce. ICSC (2013)
Yifeng Zeng, Hua Mao, Prashant Doshi, Yinghui Pan, Jian Luo
Learning Communication in Interactive Dynamic Influence Diagrams. IAT (2012)
Xia Qu, Prashant Doshi, Adam Goodie
Modeling Deep Strategic Reasoning by Humans in Competitive Games. ISAIM (2012)
Uthayasanker Thayasivam, Prashant Doshi
Improved Convergence of Iterative Ontology Alignment using Block-Coordinate Descent. AAAI (2012)

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Publication Activity (10 Years)

Top Topics

Top Venues

Prashant Doshi