Combined task and motion planning through an extensible planner-independent interface layer. - Siddharth Srivastava 001; Eugene Fang; Lorenzo Riano; Rohan Chitnis; Stuart Russell 001; Pieter Abbeel (ICRA, 2014)

Variable-Length Word Encodings for Neural Translation Models. - Rohan Chitnis; John DeNero (EMNLP, 2015)

Modular task and motion planning in belief space. - Dylan Hadfield-Menell; Edward Groshev; Rohan Chitnis; Pieter Abbeel (IROS, 2015)

Guided search for task and motion plans using learned heuristics. - Rohan Chitnis; Dylan Hadfield-Menell; Abhishek Gupta 004; Siddharth Srivastava 001; Edward Groshev; Christopher Lin; Pieter Abbeel (ICRA, 2016)

Sequential quadratic programming for task plan optimization. - Dylan Hadfield-Menell; Christopher Lin; Rohan Chitnis; Stuart Russell 001; Pieter Abbeel (IROS, 2016)

Learning What Information to Give in Partially Observed Domains. - Rohan Chitnis; Leslie Pack Kaelbling; Tomás Lozano-Pérez (CoRL, 2018)

Finding Frequent Entities in Continuous Data. - Ferran Alet; Rohan Chitnis; Leslie Pack Kaelbling; Tomás Lozano-Pérez (IJCAI, 2018)

Integrating Human-Provided Information into Belief State Representation Using Dynamic Factorization. - Rohan Chitnis; Leslie Pack Kaelbling; Tomás Lozano-Pérez (IROS, 2018)

Planning to Give Information in Partially Observed Domains with a Learned Weighted Entropy Model. - Rohan Chitnis; Leslie Pack Kaelbling; Tomás Lozano-Pérez (CoRR, 2018)

Learning Compact Models for Planning with Exogenous Processes. - Rohan Chitnis; Tomás Lozano-Pérez (CoRL, 2019)

Learning Quickly to Plan Quickly Using Modular Meta-Learning. - Rohan Chitnis; Leslie Pack Kaelbling; Tomás Lozano-Pérez (ICRA, 2019)

CAMPs: Learning Context-Specific Abstractions for Efficient Planning in Factored MDPs. - Rohan Chitnis; Tom Silver; Beomjoon Kim; Leslie Pack Kaelbling; Tomás Lozano-Pérez (CoRL, 2020)

Intrinsic Motivation for Encouraging Synergistic Behavior. - Rohan Chitnis; Shubham Tulsiani; Saurabh Gupta 001; Abhinav Gupta 001 (ICLR, 2020)

Efficient Bimanual Manipulation Using Learned Task Schemas. - Rohan Chitnis; Shubham Tulsiani; Saurabh Gupta 001; Abhinav Gupta 001 (ICRA, 2020)

GLIB: Exploration via Goal-Literal Babbling for Lifted Operator Learning. - Rohan Chitnis; Tom Silver; Joshua B. Tenenbaum; Leslie Pack Kaelbling; Tomás Lozano-Pérez (CoRR, 2020)

PDDLGym: Gym Environments from PDDL Problems. - Tom Silver; Rohan Chitnis (CoRR, 2020)

GLIB: Efficient Exploration for Relational Model-Based Reinforcement Learning via Goal-Literal Babbling. - Rohan Chitnis; Tom Silver; Joshua B. Tenenbaum; Leslie Pack Kaelbling; Tomás Lozano-Pérez (AAAI, 2021)

Planning with Learned Object Importance in Large Problem Instances using Graph Neural Networks. - Tom Silver; Rohan Chitnis; Aidan Curtis; Joshua B. Tenenbaum; Tomás Lozano-Pérez; Leslie Pack Kaelbling (AAAI, 2021)

Learning Symbolic Operators for Task and Motion Planning. - Tom Silver; Rohan Chitnis; Joshua B. Tenenbaum; Leslie Pack Kaelbling; Tomás Lozano-Pérez (IROS, 2021)

Integrated Task and Motion Planning. - Caelan Reed Garrett; Rohan Chitnis; Rachel M. Holladay; Beomjoon Kim; Tom Silver; Leslie Pack Kaelbling; Tomás Lozano-Pérez (Annu. Rev. Control. Robotics Auton. Syst., 2021)

Reinforcement Learning for Classical Planning: Viewing Heuristics as Dense Reward Generators. - Clement Gehring; Masataro Asai; Rohan Chitnis; Tom Silver; Leslie Pack Kaelbling; Shirin Sohrabi; Michael Katz 001 (ICAPS, 2022)

Towards Optimal Correlational Object Search. - Kaiyu Zheng; Rohan Chitnis; Yoonchang Sung; George Konidaris 001; Stefanie Tellex (ICRA, 2022)

Learning Neuro-Symbolic Relational Transition Models for Bilevel Planning. - Rohan Chitnis; Tom Silver; Joshua B. Tenenbaum; Tomás Lozano-Pérez; Leslie Pack Kaelbling (IROS, 2022)

Inventing Relational State and Action Abstractions for Effective and Efficient Bilevel Planning. - Tom Silver; Rohan Chitnis; Nishanth Kumar; Willie McClinton; Tomás Lozano-Pérez; Leslie Pack Kaelbling; Joshua B. Tenenbaum (CoRR, 2022)

Learning Operators with Ignore Effects for Bilevel Planning in Continuous Domains. - Nishanth Kumar; Willie McClinton; Rohan Chitnis; Tom Silver; Tomás Lozano-Pérez; Leslie Pack Kaelbling (CoRR, 2022)

Learning State and Action Abstractions for Effective and Efficient Planning - Rohan Chitnis (2022)

Predicate Invention for Bilevel Planning. - Tom Silver; Rohan Chitnis; Nishanth Kumar; Willie McClinton; Tomás Lozano-Pérez; Leslie Pack Kaelbling; Joshua B. Tenenbaum (AAAI, 2023)

Learning Efficient Abstract Planning Models that Choose What to Predict. - Nishanth Kumar; Willie McClinton; Rohan Chitnis; Tom Silver; Tomás Lozano-Pérez; Leslie Pack Kaelbling (CoRL, 2023)

Sequence Modeling is a Robust Contender for Offline Reinforcement Learning. - Prajjwal Bhargava; Rohan Chitnis; Alborz Geramifard; Shagun Sodhani; Amy Zhang 001 (CoRR, 2023)

When should we prefer Decision Transformers for Offline Reinforcement Learning? - Prajjwal Bhargava; Rohan Chitnis; Alborz Geramifard; Shagun Sodhani; Amy Zhang 001 (ICLR, 2024)

Score Models for Offline Goal-Conditioned Reinforcement Learning. - Harshit Sikchi; Rohan Chitnis; Ahmed Touati; Alborz Geramifard; Amy Zhang 001; Scott Niekum (ICLR, 2024)

IQL-TD-MPC: Implicit Q-Learning for Hierarchical Model Predictive Control. - Rohan Chitnis; Yingchen Xu; Bobak Hashemi; Lucas Lehnert; Ürün Dogan; Zheqing Zhu; Olivier Delalleau (ICRA, 2024)

Sequential Decision-Making for Inline Text Autocomplete. - Rohan Chitnis; Shentao Yang; Alborz Geramifard (RLJ, 2024)