Miao Liu

Orcid: 0000-0002-1648-8325

Affiliations:

IBM T. J. Watson Research Center,Yorktown Heights, NY, USA
MIT, Laboratory for Information and Decision Systems, Cambridge, MA, USA (former)
Duke University, Durham, NC, USA (PhD 2014)

According to our database¹, Miao Liu authored at least 44 papers between 2011 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2024

Can Large Language Models Adapt to Other Agents In-Context?

[BibT_eX]

[DOI]

CoRR, 2024

Evaluating the Prompt Steerability of Large Language Models.

[BibT_eX]

[DOI]

Erik Miehling

Michael Desmond

Karthikeyan Natesan Ramamurthy

CoRR, 2024

Contextual Moral Value Alignment Through Context-Based Aggregation.

[BibT_eX]

[DOI]

CoRR, 2024

ComVas: Contextual Moral Values Alignment System.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

2023

Learning in Factored Domains with Information-Constrained Visual Representations.

[BibT_eX]

[DOI]

CoRR, 2023

2022

Game-Theoretical Perspectives on Active Equilibria: A Preferred Solution Concept over Nash Equilibria.

[BibT_eX]

[DOI]

CoRR, 2022

AI Planning Annotation for Sample Efficient Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2022

Linearizing contextual bandits with latent state dynamics.

[BibT_eX]

[DOI]

Elliot Nelson

Debarun Bhattacharjya

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Influencing Long-Term Behavior in Multiagent Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

IDYNO: Learning Nonparametric DAGs from Interventional Dynamic Data.

[BibT_eX]

[DOI]

Tian Gao

Debarun Bhattacharjya

Elliot Nelson

Miao Liu

Yue Yu

Proceedings of the International Conference on Machine Learning, 2022

Cost-Efficient Reinforcement Learning for Optimal Trade Execution on Dynamic Market Environment.

[BibT_eX]

[DOI]

Proceedings of the 3rd ACM International Conference on AI in Finance, 2022

Context-Specific Representation Abstraction for Deep Option Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Modeling Capacity-Limited Decision Making Using a Variational Autoencoder.

[BibT_eX]

[DOI]

Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021

Capacity-Limited Decentralized Actor-Critic for Multi-Agent Games.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE Conference on Games (CoG), 2021

RL Generalization in a Theory of Mind Game Through a Sleep Metaphor (Student Abstract).

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Consolidation via Policy Information Regularization in Deep RL for Multi-Agent Games.

[BibT_eX]

[DOI]

CoRR, 2020

Deep RL With Information Constrained Policies: Generalization in Continuous Control.

[BibT_eX]

[DOI]

CoRR, 2020

Learning Hierarchical Teaching Policies for Cooperative Agents.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

On the Role of Weight Sharing During Deep Option Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Automatic Pan-Tilt Camera Control for Learning Dirichlet Process Gaussian Process (DPGP) Mixture Models of Multiple Moving Targets.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2019

Learning Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2019

Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Learning to Teach in Cooperative Multiagent Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Learning Abstract Options.

[BibT_eX]

[DOI]

Matthew Riemer

Miao Liu

Gerald Tesauro

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Eigenoption Discovery through the Deep Successor Representation.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

The Eigenoption-Critic Framework.

[BibT_eX]

[DOI]

CoRR, 2017

Learning for multi-robot cooperation in partially observable stochastic environments with macro-actions.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017

Socially aware motion planning with deep reinforcement learning.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017

Semantic-level decentralized multi-robot decision-making using probabilistic macro-observations.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Scalable accelerated decentralized multi-robot policy search in continuous observation spaces.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Decentralized non-communicating multiagent collision avoidance with deep reinforcement learning.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Quickest change detection approach to optimal control in Markov decision processes with model changes.

[BibT_eX]

[DOI]

Taposh Banerjee

Miao Liu

Jonathan P. How

Proceedings of the 2017 American Control Conference, 2017

2016

Information value in nonparametric Dirichlet-process Gaussian-process (DPGP) mixture models.

[BibT_eX]

[DOI]

Autom., 2016

Reports of the AAAI 2016 Spring Symposium Series.

[BibT_eX]

[DOI]

AI Mag., 2016

Motion planning with diffusion maps.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

Augmented dictionary learning for motion prediction.

[BibT_eX]

[DOI]

Yu Fan Chen

Miao Liu

Jonathan P. How

Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Learning for Decentralized Control of Multiagent Systems in Large, Partially-Observable Stochastic Environments.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Stick-Breaking Policy Learning in Dec-POMDPs.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

2014

Efficient Bayesian Nonparametric Methods for Model-Free Reinforcement Learning in Centralized and Decentralized Sequential Environments.

[BibT_eX]

[DOI]

Miao Liu

PhD thesis, 2014

2013

Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture

[BibT_eX]

[DOI]

CoRR, 2013

Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Online Expectation Maximization for Reinforcement Learning in POMDPs.

[BibT_eX]

[DOI]

Miao Liu

Xuejun Liao

Lawrence Carin

Proceedings of the IJCAI 2013, 2013

2011

The Infinite Regionalized Policy Representation.

[BibT_eX]

[DOI]

Miao Liu