The Infinite Regionalized Policy Representation. - Miao Liu 001; Xuejun Liao; Lawrence Carin (ICML, 2011)

Online Expectation Maximization for Reinforcement Learning in POMDPs. - Miao Liu 001; Xuejun Liao; Lawrence Carin (IJCAI, 2013)

Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture. - Trevor Campbell; Miao Liu 001; Brian Kulis; Jonathan P. How; Lawrence Carin (NIPS, 2013)

Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture - Trevor Campbell; Miao Liu 001; Brian Kulis; Jonathan P. How (CoRR, 2013)

Efficient Bayesian Nonparametric Methods for Model-Free Reinforcement Learning in Centralized and Decentralized Sequential Environments. - Miao Liu 001 (2014)

Stick-Breaking Policy Learning in Dec-POMDPs. - Miao Liu 001; Christopher Amato; Xuejun Liao; Lawrence Carin; Jonathan P. How (IJCAI, 2015)

Learning for Decentralized Control of Multiagent Systems in Large, Partially-Observable Stochastic Environments. - Miao Liu 001; Christopher Amato; Emily P. Anesta; John Daniel Griffith; Jonathan P. How (AAAI, 2016)

Augmented dictionary learning for motion prediction. - Yu Fan Chen; Miao Liu 001; Jonathan P. How (ICRA, 2016)

Motion planning with diffusion maps. - Yu Fan Chen; Shih-Yuan Liu; Miao Liu 001; Justin Miller; Jonathan P. How (IROS, 2016)

Reports of the AAAI 2016 Spring Symposium Series. - Christopher Amato; Ofra Amir; Joanna Bryson; Barbara J. Grosz; Bipin Indurkhya; Emre Kiciman; Takashi Kido; William F. Lawless; Miao Liu 001; Braden McDorman; Ross Mead; Frans A. Oliehoek; et al. (AI Mag., 2016)

Information value in nonparametric Dirichlet-process Gaussian-process (DPGP) mixture models. - Hongchuan Wei; Wenjie Lu; Pingping Zhu; Silvia Ferrari; Miao Liu 001; Robert H. Klein; Shayegan Omidshafiei; Jonathan P. How (Autom., 2016)

Quickest change detection approach to optimal control in Markov decision processes with model changes. - Taposh Banerjee; Miao Liu 001; Jonathan P. How (ACC, 2017)

Decentralized non-communicating multiagent collision avoidance with deep reinforcement learning. - Yu Fan Chen; Miao Liu 001; Michael Everett; Jonathan P. How (ICRA, 2017)

Scalable accelerated decentralized multi-robot policy search in continuous observation spaces. - Shayegan Omidshafiei; Christopher Amato; Miao Liu 001; Michael Everett; Jonathan P. How; John Vian (ICRA, 2017)

Semantic-level decentralized multi-robot decision-making using probabilistic macro-observations. - Shayegan Omidshafiei; Shih-Yuan Liu; Michael Everett; Brett Thomas Lopez; Christopher Amato; Miao Liu 001; Jonathan P. How; John Vian (ICRA, 2017)

Socially aware motion planning with deep reinforcement learning. - Yu Fan Chen; Michael Everett; Miao Liu 001; Jonathan P. How (IROS, 2017)

Learning for multi-robot cooperation in partially observable stochastic environments with macro-actions. - Miao Liu 001; Kavinayan Sivakumar; Shayegan Omidshafiei; Christopher Amato; Jonathan P. How (IROS, 2017)

The Eigenoption-Critic Framework. - Miao Liu 001; Marlos C. Machado; Gerald Tesauro; Murray Campbell (CoRR, 2017)

Eigenoption Discovery through the Deep Successor Representation. - Marlos C. Machado; Clemens Rosenbaum; Xiaoxiao Guo; Miao Liu 001; Gerald Tesauro; Murray Campbell (ICLR (Poster), 2018)

Learning Abstract Options. - Matthew Riemer; Miao Liu 001; Gerald Tesauro (NeurIPS, 2018)

Learning to Teach in Cooperative Multiagent Reinforcement Learning. - Shayegan Omidshafiei; Dong-Ki Kim; Miao Liu 001; Gerald Tesauro; Matthew Riemer; Christopher Amato; Murray Campbell; Jonathan P. How (AAAI, 2019)

Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference. - Matthew Riemer; Ignacio Cases; Robert Ajemian; Miao Liu 001; Irina Rish; Yuhai Tu; Gerald Tesauro (ICLR (Poster), 2019)

Learning Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning. - Dong-Ki Kim; Miao Liu 001; Shayegan Omidshafiei; Sebastian Lopez-Cot; Matthew Riemer; Golnaz Habibi; Gerald Tesauro; Sami Mourad; Murray Campbell; Jonathan P. How (CoRR, 2019)

Automatic Pan-Tilt Camera Control for Learning Dirichlet Process Gaussian Process (DPGP) Mixture Models of Multiple Moving Targets. - Hongchuan Wei; Pingping Zhu; Miao Liu 001; Jonathan P. How; Silvia Ferrari (IEEE Trans. Autom. Control., 2019)

On the Role of Weight Sharing During Deep Option Learning. - Matthew Riemer; Ignacio Cases; Clemens Rosenbaum; Miao Liu 001; Gerald Tesauro (AAAI, 2020)

Learning Hierarchical Teaching Policies for Cooperative Agents. - Dong-Ki Kim; Miao Liu 001; Shayegan Omidshafiei; Sebastian Lopez-Cot; Matthew Riemer; Golnaz Habibi; Gerald Tesauro; Sami Mourad; Murray Campbell; Jonathan P. How (AAMAS, 2020)

Deep RL With Information Constrained Policies: Generalization in Continuous Control. - Tyler Malloy; Chris R. Sims; Tim Klinger; Miao Liu 001; Matthew Riemer; Gerald Tesauro (CoRR, 2020)

Consolidation via Policy Information Regularization in Deep RL for Multi-Agent Games. - Tyler Malloy; Tim Klinger; Miao Liu 001; Matthew Riemer; Gerald Tesauro; Chris R. Sims (CoRR, 2020)

RL Generalization in a Theory of Mind Game Through a Sleep Metaphor (Student Abstract). - Tyler Malloy; Tim Klinger; Miao Liu 001; Gerald Tesauro; Matthew Riemer; Chris R. Sims (AAAI, 2021)

Capacity-Limited Decentralized Actor-Critic for Multi-Agent Games. - Tyler Malloy; Chris R. Sims; Tim Klinger; Miao Liu 001; Matthew Riemer; Gerald Tesauro (CoG, 2021)

Modeling Capacity-Limited Decision Making Using a Variational Autoencoder. - Tyler Malloy; Tim Klinger; Miao Liu 001; Gerald Tesauro; Matthew Riemer; Chris R. Sims (CogSci, 2021)

A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning. - Dong-Ki Kim; Miao Liu 001; Matthew Riemer; Chuangchuang Sun; Marwa Abdulhai; Golnaz Habibi; Sebastian Lopez-Cot; Gerald Tesauro; Jonathan P. How (ICML, 2021)

Context-Specific Representation Abstraction for Deep Option Learning. - Marwa Abdulhai; Dong-Ki Kim; Matthew Riemer; Miao Liu 001; Gerald Tesauro; Jonathan P. How (AAAI, 2022)

Cost-Efficient Reinforcement Learning for Optimal Trade Execution on Dynamic Market Environment. - Di Chen 001; Yada Zhu; Miao Liu 001; Jianbo Li (ICAIF, 2022)

IDYNO: Learning Nonparametric DAGs from Interventional Dynamic Data. - Tian Gao; Debarun Bhattacharjya; Elliot Nelson; Miao Liu 001; Yue Yu (ICML, 2022)

Influencing Long-Term Behavior in Multiagent Reinforcement Learning. - Dong-Ki Kim; Matthew Riemer; Miao Liu 001; Jakob N. Foerster; Michael Everett; Chuangchuang Sun; Gerald Tesauro; Jonathan P. How (NeurIPS, 2022)

Linearizing contextual bandits with latent state dynamics. - Elliot Nelson; Debarun Bhattacharjya; Tian Gao; Miao Liu 001; Djallel Bouneffouf 001; Pascal Poupart (UAI, 2022)

AI Planning Annotation for Sample Efficient Reinforcement Learning. - Junkyu Lee 001; Michael Katz 001; Don Joven Agravante; Miao Liu 001; Tim Klinger; Murray Campbell; Shirin Sohrabi; Gerald Tesauro (CoRR, 2022)

Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Stochastic Approach. - Heshan Devaka Fernando; Han Shen; Miao Liu 001; Subhajit Chaudhury; Keerthiram Murugesan; Tianyi Chen (CoRR, 2022)

Game-Theoretical Perspectives on Active Equilibria: A Preferred Solution Concept over Nash Equilibria. - Dong-Ki Kim; Matthew Riemer; Miao Liu 001; Jakob N. Foerster; Gerald Tesauro; Jonathan P. How (CoRR, 2022)

Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks. - Shuai Zhang 015; Meng Wang 003; Pin-Yu Chen; Sijia Liu 001; Songtao Lu; Miao Liu 001 (ICLR, 2023)

Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Approach. - Heshan Devaka Fernando; Han Shen; Miao Liu 001; Subhajit Chaudhury; Keerthiram Murugesan; Tianyi Chen (ICLR, 2023)

On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration. - Shuai Zhang 015; Hongkang Li; Meng Wang 003; Miao Liu 001; Pin-Yu Chen; Songtao Lu; Sijia Liu 001; Keerthiram Murugesan; Subhajit Chaudhury (NeurIPS, 2023)

Learning in Factored Domains with Information-Constrained Visual Representations. - Tyler Malloy; Miao Liu 001; Matthew D. Riemer; Tim Klinger; Gerald Tesauro; Chris R. Sims (CoRR, 2023)

Variance Reduction Can Improve Trade-Off in Multi-Objective Learning. - Heshan Devaka Fernando; Lisha Chen; Songtao Lu; Pin-Yu Chen; Miao Liu 001; Subhajit Chaudhury; Keerthiram Murugesan; Gaowen Liu; Meng Wang 003; Tianyi Chen (ICASSP, 2024)

SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning. - Shuai Zhang 015; Heshan Devaka Fernando; Miao Liu 001; Keerthiram Murugesan; Songtao Lu; Pin-Yu Chen; Tianyi Chen; Meng Wang 003 (ICML, 2024)

ComVas: Contextual Moral Values Alignment System. - Inkit Padhi; Pierre L. Dognin; Jesus Rios; Ronny Luss; Swapnaja Achintalwar; Matthew Riemer; Miao Liu 001; Prasanna Sattigeri; Manish Nagireddy; Kush R. Varshney; Djallel Bouneffouf 001 (IJCAI, 2024)

Contextual Moral Value Alignment Through Context-Based Aggregation. - Pierre L. Dognin; Jesus Rios; Ronny Luss; Inkit Padhi; Matthew D. Riemer; Miao Liu 001; Prasanna Sattigeri; Manish Nagireddy; Kush R. Varshney; Djallel Bouneffouf 001 (CoRR, 2024)

Evaluating the Prompt Steerability of Large Language Models. - Erik Miehling; Michael Desmond; Karthikeyan Natesan Ramamurthy; Elizabeth M. Daly; Pierre L. Dognin; Jesus Rios; Djallel Bouneffouf 001; Miao Liu 001 (CoRR, 2024)

Can Large Language Models Adapt to Other Agents In-Context? - Matthew Riemer; Zahra Ashktorab; Djallel Bouneffouf 001; Payel Das; Miao Liu 001; Justin D. Weisz; Murray Campbell (CoRR, 2024)

Q-function Decomposition with Intervention Semantics for Factored Action Spaces. - Junkyu Lee 001; Tian Gao; Elliot Nelson; Miao Liu 001; Debarun Bhattacharjya; Songtao Lu (AISTATS, 2025)

Contextual Value Alignment. - Pierre Dognin; Jesus Rios; Ronny Luss; Prasanna Sattigeri; Miao Liu 001; Inkit Padhi; Matthew Riemer; Manish Nagireddy; Kush R. Varshney; Djallel Bouneffouf 001 (ICASSP, 2025)

Evaluating the Prompt Steerability of Large Language Models. - Erik Miehling; Michael Desmond; Karthikeyan Natesan Ramamurthy; Elizabeth M. Daly; Kush R. Varshney; Eitan Farchi; Pierre Dognin; Jesus Rios; Djallel Bouneffouf 001; Miao Liu 001; Prasanna Sattigeri (NAACL (Long Papers), 2025)