Miao Liu

ORCID

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 46

Top Venues

Duke University, Durham, NC, USA (PHD)

Education History

Duke University, Durham, NC, USA

PHD

Publications

Pierre L. Dognin, Jesus Rios, Ronny Luss, Inkit Padhi, Matthew D. Riemer, Miao Liu, Prasanna Sattigeri, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf
Contextual Moral Value Alignment Through Context-Based Aggregation. CoRR (2024)
Tyler Malloy, Miao Liu, Matthew D. Riemer, Tim Klinger, Gerald Tesauro, Chris R. Sims
Learning in Factored Domains with Information-Constrained Visual Representations. CoRR (2023)
Dong-Ki Kim, Matthew Riemer, Miao Liu, Jakob N. Foerster, Michael Everett, Chuangchuang Sun, Gerald Tesauro, Jonathan P. How
Influencing Long-Term Behavior in Multiagent Reinforcement Learning. NeurIPS (2022)
Junkyu Lee, Michael Katz, Don Joven Agravante, Miao Liu, Tim Klinger, Murray Campbell, Shirin Sohrabi, Gerald Tesauro
AI Planning Annotation for Sample Efficient Reinforcement Learning. CoRR (2022)
Dong-Ki Kim, Matthew Riemer, Miao Liu, Jakob N. Foerster, Michael Everett, Chuangchuang Sun, Gerald Tesauro, Jonathan P. How
Influencing Long-Term Behavior in Multiagent Reinforcement Learning. CoRR (2022)
Dong-Ki Kim, Matthew Riemer, Miao Liu, Jakob N. Foerster, Gerald Tesauro, Jonathan P. How
Game-Theoretical Perspectives on Active Equilibria: A Preferred Solution Concept over Nash Equilibria. CoRR (2022)
Marwa Abdulhai, Dong-Ki Kim, Matthew Riemer, Miao Liu, Gerald Tesauro, Jonathan P. How
Context-Specific Representation Abstraction for Deep Option Learning. AAAI (2022)
Tyler Malloy, Chris R. Sims, Tim Klinger, Miao Liu, Matthew Riemer, Gerald Tesauro
Capacity-Limited Decentralized Actor-Critic for Multi-Agent Games. CoG (2021)
Tyler Malloy, Tim Klinger, Miao Liu, Gerald Tesauro, Matthew Riemer, Chris R. Sims
RL Generalization in a Theory of Mind Game Through a Sleep Metaphor (Student Abstract). AAAI (2021)
Dong-Ki Kim, Miao Liu, Matthew Riemer, Chuangchuang Sun, Marwa Abdulhai, Golnaz Habibi, Sebastian Lopez-Cot, Gerald Tesauro, Jonathan P. How
A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning. ICML (2021)
Tyler Malloy, Tim Klinger, Miao Liu, Gerald Tesauro, Matthew Riemer, Chris R. Sims
Modeling Capacity-Limited Decision Making Using a Variational Autoencoder. CogSci (2021)
Marwa Abdulhai, Dong-Ki Kim, Matthew Riemer, Miao Liu, Gerald Tesauro, Jonathan P. How
Context-Specific Representation Abstraction for Deep Option Learning. CoRR (2021)
Tyler Malloy, Tim Klinger, Miao Liu, Matthew Riemer, Gerald Tesauro, Chris R. Sims
Consolidation via Policy Information Regularization in Deep RL for Multi-Agent Games. CoRR (2020)
Dong-Ki Kim, Miao Liu, Matthew Riemer, Chuangchuang Sun, Marwa Abdulhai, Golnaz Habibi, Sebastian Lopez-Cot, Gerald Tesauro, Jonathan P. How
A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning. CoRR (2020)
Tyler Malloy, Chris R. Sims, Tim Klinger, Miao Liu, Matthew Riemer, Gerald Tesauro
Deep RL With Information Constrained Policies: Generalization in Continuous Control. CoRR (2020)
Matthew Riemer, Ignacio Cases, Clemens Rosenbaum, Miao Liu, Gerald Tesauro
On the Role of Weight Sharing During Deep Option Learning. AAAI (2020)
Dong-Ki Kim, Miao Liu, Shayegan Omidshafiei, Sebastian Lopez-Cot, Matthew Riemer, Golnaz Habibi, Gerald Tesauro, Sami Mourad, Murray Campbell, Jonathan P. How
Learning Hierarchical Teaching Policies for Cooperative Agents. AAMAS (2020)
Dong-Ki Kim, Miao Liu, Shayegan Omidshafiei, Sebastian Lopez-Cot, Matthew Riemer, Golnaz Habibi, Gerald Tesauro, Sami Mourad, Murray Campbell, Jonathan P. How
Learning Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning. CoRR (2019)
Matthew Riemer, Ignacio Cases, Clemens Rosenbaum, Miao Liu, Gerald Tesauro
On the Role of Weight Sharing During Deep Option Learning. CoRR (2019)
Hongchuan Wei, Pingping Zhu, Miao Liu, Jonathan P. How, Silvia Ferrari
Automatic Pan-Tilt Camera Control for Learning Dirichlet Process Gaussian Process (DPGP) Mixture Models of Multiple Moving Targets. IEEE Trans. Autom. Control. 64 (1) (2019)
Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu, Gerald Tesauro
Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference. ICLR (Poster) (2019)
Shayegan Omidshafiei, Dong-Ki Kim, Miao Liu, Gerald Tesauro, Matthew Riemer, Christopher Amato, Murray Campbell, Jonathan P. How
Learning to Teach in Cooperative Multiagent Reinforcement Learning. AAAI (2019)
Matthew Riemer, Miao Liu, Gerald Tesauro
Learning Abstract Options. CoRR (2018)
Marlos C. Machado, Clemens Rosenbaum, Xiaoxiao Guo, Miao Liu, Gerald Tesauro, Murray Campbell
Eigenoption Discovery through the Deep Successor Representation. ICLR (Poster) (2018)
Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu, Gerald Tesauro
Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference. CoRR (2018)
Matthew Riemer, Miao Liu, Gerald Tesauro
Learning Abstract Options. NeurIPS (2018)
Shayegan Omidshafiei, Dong-Ki Kim, Miao Liu, Gerald Tesauro, Matthew Riemer, Christopher Amato, Murray Campbell, Jonathan P. How
Learning to Teach in Cooperative Multiagent Reinforcement Learning. CoRR (2018)
Shayegan Omidshafiei, Christopher Amato, Miao Liu, Michael Everett, Jonathan P. How, John Vian
Scalable Accelerated Decentralized Multi-Robot Policy Search in Continuous Observation Spaces. CoRR (2017)
Miao Liu, Kavinayan Sivakumar, Shayegan Omidshafiei, Christopher Amato, Jonathan P. How
Learning for Multi-robot Cooperation in Partially Observable Stochastic Environments with Macro-actions. CoRR (2017)
Taposh Banerjee, Miao Liu, Jonathan P. How
Quickest change detection approach to optimal control in Markov decision processes with model changes. ACC (2017)
Shayegan Omidshafiei, Shih-Yuan Liu, Michael Everett, Brett Thomas Lopez, Christopher Amato, Miao Liu, Jonathan P. How, John Vian
Semantic-level Decentralized Multi-Robot Decision-Making using Probabilistic Macro-Observations. CoRR (2017)
Miao Liu, Marlos C. Machado, Gerald Tesauro, Murray Campbell
The Eigenoption-Critic Framework. CoRR (2017)
Yu Fan Chen, Michael Everett, Miao Liu, Jonathan P. How
Socially Aware Motion Planning with Deep Reinforcement Learning. CoRR (2017)
Marlos C. Machado, Clemens Rosenbaum, Xiaoxiao Guo, Miao Liu, Gerald Tesauro, Murray Campbell
Eigenoption Discovery through the Deep Successor Representation. CoRR (2017)
Yu Fan Chen, Michael Everett, Miao Liu, Jonathan P. How
Socially aware motion planning with deep reinforcement learning. IROS (2017)
Shayegan Omidshafiei, Christopher Amato, Miao Liu, Michael Everett, Jonathan P. How, John Vian
Scalable accelerated decentralized multi-robot policy search in continuous observation spaces. ICRA (2017)
Miao Liu, Kavinayan Sivakumar, Shayegan Omidshafiei, Christopher Amato, Jonathan P. How
Learning for multi-robot cooperation in partially observable stochastic environments with macro-actions. IROS (2017)
Shayegan Omidshafiei, Shih-Yuan Liu, Michael Everett, Brett Thomas Lopez, Christopher Amato, Miao Liu, Jonathan P. How, John Vian
Semantic-level decentralized multi-robot decision-making using probabilistic macro-observations. ICRA (2017)
Yu Fan Chen, Miao Liu, Michael Everett, Jonathan P. How
Decentralized non-communicating multiagent collision avoidance with deep reinforcement learning. ICRA (2017)
Yu Fan Chen, Miao Liu, Jonathan P. How
Augmented dictionary learning for motion prediction. ICRA (2016)
Yu Fan Chen, Shih-Yuan Liu, Miao Liu, Justin Miller, Jonathan P. How
Motion planning with diffusion maps. IROS (2016)
Christopher Amato, Ofra Amir, Joanna Bryson, Barbara J. Grosz, Bipin Indurkhya, Emre Kiciman, Takashi Kido, William F. Lawless, Miao Liu, Braden McDorman, Ross Mead, Frans A. Oliehoek, Andrew Specian, Georgi Stojanov, Keiki Takadama
Reports of the AAAI 2016 Spring Symposium Series. AI Mag. 37 (4) (2016)
Miao Liu, Christopher Amato, Emily P. Anesta, John Daniel Griffith, Jonathan P. How
Learning for Decentralized Control of Multiagent Systems in Large, Partially-Observable Stochastic Environments. AAAI (2016)
Hongchuan Wei, Wenjie Lu, Pingping Zhu, Silvia Ferrari, Miao Liu, Robert H. Klein, Shayegan Omidshafiei, Jonathan P. How
Information value in nonparametric Dirichlet-process Gaussian-process (DPGP) mixture models. Autom. 74 (2016)
Yu Fan Chen, Miao Liu, Michael Everett, Jonathan P. How
Decentralized Non-communicating Multiagent Collision Avoidance with Deep Reinforcement Learning. CoRR (2016)
Taposh Banerjee, Miao Liu, Jonathan P. How
Quickest Change Detection Approach to Optimal Control in Markov Decision Processes with Model Changes. CoRR (2016)
Miao Liu, Christopher Amato, Xuejun Liao, Lawrence Carin, Jonathan P. How
Stick-Breaking Policy Learning in Dec-POMDPs. IJCAI (2015)
Miao Liu, Christopher Amato, Xuejun Liao, Lawrence Carin, Jonathan P. How
Stick-Breaking Policy Learning in Dec-POMDPs. CoRR (2015)
Trevor Campbell, Miao Liu, Brian Kulis, Jonathan P. How, Lawrence Carin
Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture. NIPS (2013)
Miao Liu, Xuejun Liao, Lawrence Carin
Online Expectation Maximization for Reinforcement Learning in POMDPs. IJCAI (2013)
Trevor Campbell, Miao Liu, Brian Kulis, Jonathan P. How
Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture CoRR (2013)
Miao Liu, Xuejun Liao, Lawrence Carin
The Infinite Regionalized Policy Representation. ICML (2011)

Miao Liu.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Miao Liu