Pradeep Varakantham

ORCID

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 108

Top Venues

Publications

Changyu Chen, Zichen Liu, Chao Du, Tianyu Pang, Qian Liu, Arunesh Sinha, Pradeep Varakantham, Min Lin
Bootstrapping Language Models with DPO Implicit Rewards. CoRR (2024)
Hao Jiang, Tien Mai, Pradeep Varakantham, Huy Hoang
Reward Penalties on Augmented States for Solving Richly Constrained RL Effectively. AAAI (2024)
Sidney Tio, Dexun Li, Pradeep Varakantham
EduQate: Generating Adaptive Curricula through RMABs in Education Settings. CoRR (2024)
Roman Belaire, Arunesh Sinha, Pradeep Varakantham
Probabilistic Perspectives on Error Minimization in Adversarial Reinforcement Learning. CoRR (2024)
Wenjun Li, Pradeep Varakantham
Unsupervised Training Sequence Design: Efficient and Generalizable Agent Training. AAAI (2024)
Qian Shao, Pradeep Varakantham, Shih-Fen Cheng
Imitating Cost-Constrained Behaviors in Reinforcement Learning. ICAPS (2024)
Shashank Reddy Chirra, Pradeep Varakantham, Praveen Paruchuri
Preserving the Privacy of Reward Functions in MDPs through Deception. CoRR (2024)
Wenjun Li, Changyu Chen, Pradeep Varakantham
Unlocking Large Language Model's Planning Capabilities with Maximum Diversity Fine-tuning. CoRR (2024)
Roman Belaire, Pradeep Varakantham, Thanh Hong Nguyen, David Lo
Regret-based Defense in Adversarial Reinforcement Learning. AAMAS (2024)
Shashank Reddy Chirra, Pradeep Varakantham, Praveen Paruchuri
Safety through feedback in Constrained RL. CoRR (2024)
Yuxiao Lu, Arunesh Sinha, Pradeep Varakantham
Handling Long and Richly Constrained Tasks through Constrained Hierarchical Reinforcement Learning. AAAI (2024)
Huy Hoang, Tien Mai, Pradeep Varakantham
Imitate the Good and Avoid the Bad: An Incremental Approach to Safe Reinforcement Learning. AAAI (2024)
Jayden Teoh Jing Teoh, Wenjun Li, Pradeep Varakantham
Unifying Regret and State-Action Space Coverage for Effective Unsupervised Environment Design. AAMAS (2024)
Qian Shao, Pradeep Varakantham, Shih-Fen Cheng
Imitating Cost-Constrained Behaviors in Reinforcement Learning. CoRR (2024)
Changyu Chen, Shashank Reddy Chirra, Maria José Ferreira, Cleotilde Gonzalez, Arunesh Sinha, Pradeep Varakantham
Towards Neural Network based Cognitive Models of Dynamic Decision-Making by Humans. CoRR (2024)
Huy Hoang, Tien Mai, Pradeep Varakantham
SubIQ: Inverse Soft-Q Learning for Offline Imitation with Suboptimal Demonstrations. CoRR (2024)
Xianjie Zhang, Pradeep Varakantham, Hao Jiang
Future Aware Pricing and Matching for Sustainable On-Demand Ride Pooling. AAAI (2023)
Sidney Tio, Pradeep Varakantham
Transferable Curricula through Difficulty Conditioned Generators. IJCAI (2023)
Huy Hoang, Tien Mai, Pradeep Varakantham
Imitate the Good and Avoid the Bad: An Incremental Approach to Safe Reinforcement Learning. CoRR (2023)
Roman Belaire, Pradeep Varakantham, David Lo
Regret-Based Optimization for Robust Reinforcement Learning. CoRR (2023)
Changyu Chen, Ramesha Karunasena, Thanh Hong Nguyen, Arunesh Sinha, Pradeep Varakantham
Generative Modelling of Stochastic Actions with Arbitrary Constraints in Reinforcement Learning. CoRR (2023)
Pathmanathan Pankayaraj, Pradeep Varakantham
Constrained Reinforcement Learning in Hard Exploration Problems. AAAI (2023)
Dexun Li, Wenjun Li, Pradeep Varakantham
Diversity Induced Environment Design via Self-Play. CoRR (2023)
Yuxiao Lu, Pradeep Varakantham, Arunesh Sinha
Conditioning Hierarchical Reinforcement Learning on Flexible Constraints. CoRR (2023)
Avinandan Bose, Hao Jiang, Pradeep Varakantham, Zichang Ge
On Sustainable Ride Pooling Through Conditional Expected Value Decomposition. ECAI (2023)
Xianjie Zhang, Pradeep Varakantham, Hao Jiang
Future Aware Pricing and Matching for Sustainable On-demand Ride Pooling. CoRR (2023)
Wenjun Li, Pradeep Varakantham, Dexun Li
Generalization through Diversity: Improving Unsupervised Environment Design. IJCAI (2023)
Changyu Chen, Ramesha Karunasena, Thanh Hong Nguyen, Arunesh Sinha, Pradeep Varakantham
Generative Modelling of Stochastic Actions with Arbitrary Constraints in Reinforcement Learning. NeurIPS (2023)
Hao Jiang, Tien Mai, Pradeep Varakantham
Solving Constrained Reinforcement Learning through Augmented State and Reward Penalties. CoRR (2023)
Sidney Tio, Jimmy Ho, Pradeep Varakantham
Training Reinforcement Learning Agents and Humans With Difficulty-Conditioned Generators. CoRR (2023)
Rajiv Ranjan Kumar, Pradeep Varakantham, Shih-Fen Cheng
Strategic Planning for Flexible Agent Availability in Large Taxi Fleets. AAMAS (2023)
Dexun Li, Pradeep Varakantham
A Hierarchical Approach to Environment Design with Generative Trajectory Modeling. CoRR (2023)
Sidney Tio, Pradeep Varakantham
Transferable Curricula through Difficulty Conditioned Generators. CoRR (2023)
Rajiv Ranjan Kumar, Pradeep Varakantham, Shih-Fen Cheng
Strategic Planning for Flexible Agent Availability in Large Taxi Fleets. CoRR (2023)
Dexun Li, Pradeep Varakantham
Avoiding Starvation of Arms in Restless Multi-Armed Bandits. AAMAS (2023)
Jiajing Ling, Moritz Lukas Schuler, Akshat Kumar, Pradeep Varakantham
Knowledge Compilation for Constrained Combinatorial Action Spaces in Reinforcement Learning. AAMAS (2023)
Wenjun Li, Pradeep Varakantham, Dexun Li
Effective Diversity in Unsupervised Environment Design. CoRR (2023)
Tanvi Verma, Pradeep Varakantham
Learning Individual Policies in Large Multi-agent Systems through Local Variance Minimization. CoRR (2022)
Susobhan Ghosh, Pradeep Varakantham, Aniket Bhatkhande, Tamanna Ahmad, Anish Andheria, Wenjun Li, Aparna Taneja, Divy Thakkar, Milind Tambe
Facilitating Human-Wildlife Cohabitation through Conflict Prediction. AAAI (2022)
Dexun Li, Pradeep Varakantham
Efficient resource allocation with fairness constraints in restless multi-armed bandits. UAI (2022)
Dexun Li, Pradeep Varakantham
Efficient Resource Allocation with Fairness Constraints in Restless Multi-Armed Bandits. CoRR (2022)
Dexun Li, Pradeep Varakantham
Towards Soft Fairness in Restless Multi-Armed Bandits. CoRR (2022)
Aditya Mate, Lovish Madaan, Aparna Taneja, Neha Madhiwalla, Shresth Verma, Gargi Singh, Aparna Hegde, Pradeep Varakantham, Milind Tambe
Field Study in Deploying Restless Multi-Armed Bandits: Assisting Non-profits in Improving Maternal and Child Health. AAAI (2022)
Jiang Hao, Pradeep Varakantham
Hierarchical Value Decomposition for Effective On-demand Ride-Pooling. AAMAS (2022)
Sanket Shah, Meghna Lowalekar, Pradeep Varakantham
Joint Pricing and Matching for City-Scale Ride-Pooling. ICAPS (2022)
Sylvie Thiébaux, William Yeoh, Akshat Kumar, Pradeep Varakantham
Preface. ICAPS (2022)
Dexun Li, Meghna Lowalekar, Pradeep Varakantham
CLAIM: Curriculum Learning Policy for Influence Maximization in Unknown Social Networks. CoRR (2021)
Siddharth Nishtala, Lovish Madaan, Aditya Mate, Harshavardhan Kamarthi, Anirudh Grama, Divy Thakkar, Dhyanesh Narayanan, Suresh Chaudhary, Neha Madhiwalla, Ramesh Padmanabhan, Aparna Hegde, Pradeep Varakantham, Balaraman Ravindran, Milind Tambe
Selective Intervention Planning using Restless Multi-Armed Bandits to Improve Maternal and Child Health Outcomes. CoRR (2021)
Aditya Mate, Lovish Madaan, Aparna Taneja, Neha Madhiwalla, Shresth Verma, Gargi Singh, Aparna Hegde, Pradeep Varakantham, Milind Tambe
Field Study in Deploying Restless Multi-Armed Bandits: Assisting Non-Profits in Improving Maternal and Child Health. CoRR (2021)
Dexun Li, Meghna Lowalekar, Pradeep Varakantham
CLAIM: curriculum learning policy for influence maximization in unknown social networks. UAI (2021)
Avinandan Bose, Pradeep Varakantham
Conditional Expectation based Value Decomposition for Scalable On-Demand Ride Pooling. CoRR (2021)
Arpita Biswas, Gaurav Aggarwal, Pradeep Varakantham, Milind Tambe
Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcare. CoRR (2021)
Arpita Biswas, Gaurav Aggarwal, Pradeep Varakantham, Milind Tambe
Learning Index Policies for Restless Bandits with Application to Maternal Healthcare. AAMAS (2021)
Rajiv Ranjan Kumar, Pradeep Varakantham, Shih-Fen Cheng
Adaptive Operating Hours for Improved Performance of Taxi Fleets. AAMAS (2021)
Arpita Biswas, Gaurav Aggarwal, Pradeep Varakantham, Milind Tambe
Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcare. IJCAI (2021)
Susobhan Ghosh, Pradeep Varakantham, Aniket Bhatkhande, Tamanna Ahmad, Anish Andheria, Wenjun Li, Aparna Taneja, Divy Thakkar, Milind Tambe
Facilitating human-wildlife cohabitation through conflict prediction. CoRR (2021)
Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Zone pAth Construction (ZAC) based Approaches for Effective Real-Time Ridesharing. J. Artif. Intell. Res. 70 (2021)
Tanvi Verma, Pradeep Varakantham
Value Variance Minimization for Learning Approximate Equilibrium in Aggregation Systems. CoRR (2020)
Sanket Shah, Arunesh Sinha, Pradeep Varakantham, Andrew Perrault, Milind Tambe
Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning. AAAI (2020)
Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Competitive Ratios for Online Multi-capacity Ridesharing. CoRR (2020)
Sanket Shah, Meghna Lowalekar, Pradeep Varakantham
Neural Approximate Dynamic Programming for On-Demand Ride-Pooling. AAAI (2020)
Srishti Dhamija, Alolika Gon, Pradeep Varakantham, William Yeoh
Online Traffic Signal Control through Sample-Based Constrained Optimization. ICAPS (2020)
Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Zone pAth Construction (ZAC) based Approaches for Effective Real-Time Ridesharing. CoRR (2020)
Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Competitive Ratios for Online Multi-capacity Ridesharing. AAMAS (2020)
Rajiv Ranjan Kumar, Pradeep Varakantham
On Solving Cooperative MARL Problems with a Few Good Experiences. CoRR (2020)
Sanket Shah, Arunesh Sinha, Pradeep Varakantham, Andrew Perrault, Milind Tambe
Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning. CoRR (2019)
Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
ZAC: A Zone Path Construction Approach for Effective Real-Time Ridesharing. ICAPS (2019)
Abhinav Bhatia, Pradeep Varakantham, Akshat Kumar
Resource Constrained Deep Reinforcement Learning. ICAPS (2019)
Tanvi Verma, Pradeep Varakantham, Hoong Chuin Lau
Entropy Based Independent Learning in Anonymous Multi-Agent Settings. ICAPS (2019)
Chung-Kyun Han, Shih-Fen Cheng, Pradeep Varakantham
A Homophily-Free Community Detection Framework for Trajectories with Delayed Responses. AAMAS (2019)
Tanvi Verma, Pradeep Varakantham
Correlated Learning for Aggregation Systems. UAI (2019)
Sanket Shah, Meghna Lowalekar, Pradeep Varakantham
Neural Approximate Dynamic Programming for On-Demand Ride-Pooling. CoRR (2019)
Muralidhar Konda, Pradeep Varakantham, Aayush Saxena, Meghna Lowalekar
RE-ORG: An Online Repositioning Guidance Agent. AAMAS (2019)
Shashi Shekhar Jha, Shih-Fen Cheng, Meghna Lowalekar, Nicholas Wong, Rishikeshan Rajendram, Pradeep Varakantham, Nghia Troung Troung, Firmansyah Bin Abd Rahman
A Driver Guidance System for Taxis in Singapore. AAMAS (2018)
Pritee Agrawal, Pradeep Varakantham, William Yeoh
Decentralized Planning for Non-dedicated Agent Teams with Submodular Rewards in Uncertain Environments. UAI (2018)
Supriyo Ghosh, Pradeep Varakantham
Dispatch Guided Allocation Optimization for Effective Emergency Response. AAAI (2018)
Muralidhar Konda, Supriyo Ghosh, Pradeep Varakantham
Reserved Optimisation: Handling Incident Priorities in Emergency Response Systems. ICAPS (2018)
Pradeep Varakantham, Akshat Kumar, Hoong Chuin Lau, William Yeoh
Risk-Sensitive Stochastic Orienteering Problems for Trip Optimization in Urban Environments. ACM Trans. Intell. Syst. Technol. 9 (3) (2018)
Shashi Shekhar Jha, Shih-Fen Cheng, Meghna Lowalekar, Nicholas Wong, Rishikeshan Rajendram, Trong Khiem Tran, Pradeep Varakantham, Trong Nghia Truong, Firmansyah Bin Abd Rahman
Upping the Game of Taxi Driving in the Age of Uber. AAAI (2018)
Srishti Dhamija, Pradeep Varakantham
TuSeRACT: Turn-Sample-Based Real-Time Traffic Signal Control. CoRR (2018)
Tanvi Verma, Pradeep Varakantham, Hoong Chuin Lau
Entropy Controlled Non-Stationarity for Improving Performance of Independent Learners in Anonymous MARL Settings. CoRR (2018)
Pallavi Manohar, Pradeep Varakantham, Hoong Chuin Lau
Bounded Rank Optimization for Effective and Efficient Emergency Response. ICAPS (2018)
Abhinav Bhatia, Pradeep Varakantham, Akshat Kumar
Resource Constrained Deep Reinforcement Learning. CoRR (2018)
Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Online spatio-temporal matching in stochastic and dynamic domains. Artif. Intell. 261 (2018)
Supriyo Ghosh, Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet
Dynamic Repositioning to Reduce Lost Demand in Bike Sharing Systems. J. Artif. Intell. Res. 58 (2017)
Meghna Lowalekar, Pradeep Varakantham, Supriyo Ghosh, Sanjay Dominik Jena, Patrick Jaillet
Online Repositioning in Bike Sharing Systems. ICAPS (2017)
Rajiv Ranjan Kumar, Pradeep Varakantham
Exploiting Anonymity and Homogeneity in Factored Dec-MDPs through Precomputed Binomial Distributions. AAMAS (2017)
Tanvi Verma, Pradeep Varakantham, Sarit Kraus, Hoong Chuin Lau
Augmenting Decisions of Taxi Drivers through Reinforcement Learning for Improving Revenues. ICAPS (2017)
Asrar Ahmed, Pradeep Varakantham, Meghna Lowalekar, Yossiri Adulyasak, Patrick Jaillet
Sampling Based Approaches for Minimizing Regret in Uncertain Markov Decision Processes (MDPs). J. Artif. Intell. Res. 59 (2017)
Supriyo Ghosh, Pradeep Varakantham
Incentivizing the Use of Bike Trailers for Dynamic Repositioning in Bike Sharing Systems. ICAPS (2017)
Rajiv Ranjan Kumar, Pradeep Varakantham, Akshat Kumar
Decentralized Planning in Stochastic Environments with Submodular Rewards. AAAI (2017)
Pradeep Varakantham, Bo An, Bryan Low, Jie Zhang
Artificial Intelligence Research in Singapore: Assisting the Development of a Smart Nation. AI Mag. 38 (3) (2017)
Pritee Agrawal, Pradeep Varakantham
Proactive and Reactive Coordination of Non-dedicated Agent Teams Operating in Uncertain Environments. IJCAI (2017)
Pradeep Varakantham, Na Fu
Mechanism Design for Strategic Project Scheduling. IJCAI (2017)
Supriyo Ghosh, Michael A. Trick, Pradeep Varakantham
Robust Repositioning to Counter Unpredictable Demand in Bike Sharing Systems. IJCAI (2016)
Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Online Spatio-Temporal Matching in Stochastic and Dynamic Domains. AAAI (2016)
Ping Hou, William Yeoh, Pradeep Varakantham
Solving Risk-Sensitive POMDPs With and Without Cost Observations. AAAI (2016)
Soujanya Lanka, Deepika Pathania, Pooja Kushalappa, Pradeep Varakantham
NLU Framework for Voice Enabling Non-Native Applications on Smart Devices. AAAI (2016)
Hoong Chuin Lau, Aldy Gunawan, Pradeep Varakantham, Wenjie Wang
PRESS: PeRsonalized Event Scheduling recommender System (Demonstration). AAMAS (2016)
Radhika Arava, Pradeep Varakantham
Detecting Communities Using Coordination Games: A Short Paper. ECAI (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Pradeep Varakantham