Mark K. Ho

63 papers A* 11B 22Journal 28Unranked 2
YearRankTypeTitle / Venue / Authors
2025 J jnl
Estimating cognitive biases with attention-aware inverse planning.
CoRR
Sounak Banerjee, Daphne Cornelisse, Deepak Edakkattil Gopinath, Emily Sumner, Jonathan A. DeCastro, Guy Rosman, Eugene Vinitsky, Mark K. Ho
2025 B conf
Integration of Language and Experience via the Instructed Bandit Task.
CogSci
Ellen Su, Mark K. Ho, Todd M. Gureckis
2025 B conf
Learning about Inductive Potential from Generic Statements.
CogSci
Marianna Y. Zhang, Sarah-Jane Leslie, Marjorie Rhodes, Mark K. Ho
2024 J jnl
Building Machines that Learn and Think with People.
CoRR
Katherine M. Collins, Ilia Sucholutsky, Umang Bhatt, Kartik Chandra, Lionel Wong, Mina Lee, Cedegao E. Zhang, Tan Zhi-Xuan, Mark K. Ho, Vikash Mansinghka, Adrian Weller, Joshua B. Tenenbaum, Thomas L. Griffiths
2024 B conf
Common sense reasoning about credibility.
CogSci
Peiyao Hu, Mark K. Ho
2024 B conf
Concept Alignment as a Prerequisite for Value Alignment.
CogSci
Sunayana Rane, Mark K. Ho, Ilia Sucholutsky, Tom Griffiths
2024 B conf
Investigating Flexible Role Binding in AI Agents.
CogSci
Brian Pennisi, Todd M. Gureckis, Rheza Budiono, Mark K. Ho
2024 B conf
Modeling Cognitive Strategies in Teaching: Integrating Theory of Mind and Heuristics.
CogSci
Sevan K. Harootonian, Yael Niv, Tom Griffiths, Mark K. Ho
2024 J jnl
Representational Alignment Supports Effective Machine Teaching.
CoRR
Ilia Sucholutsky, Katherine M. Collins, Maya Malaviya, Nori Jacoby, Weiyang Liu, Theodore R. Sumers, Michalis Korakakis, Umang Bhatt, Mark K. Ho, Joshua B. Tenenbaum, Bradley C. Love, Zachary A. Pardos, Adrian Weller, Thomas L. Griffiths
2024 A* conf
Structurally Guided Task Decomposition in Spatial Navigation Tasks (Student Abstract).
AAAI
Ruiqi He, Carlos G. Correa, Tom Griffiths, Mark K. Ho
2024 — conf
Teaching Functions with Gaussian Process Regression.
AAAI Spring Symposia
Maya Malaviya, Mark K. Ho
2024 B conf
Teaching Functions with Gaussian Process Regression.
CogSci
Maya Malaviya, Mark K. Ho
2024 J jnl
Three Dogmas of Reinforcement Learning.
RLJ
David Abel, Mark K. Ho, Anna Harutyunyan
2024 J jnl
Three Dogmas of Reinforcement Learning.
CoRR
David Abel, Mark K. Ho, Anna Harutyunyan
2023 J jnl
Bayesian Reinforcement Learning with Limited Cognitive Load.
CoRR
Dilip Arumugam, Mark K. Ho, Noah D. Goodman, Benjamin Van Roy
2023 J jnl
Concept Alignment as a Prerequisite for Value Alignment.
CoRR
Sunayana Rane, Mark K. Ho, Ilia Sucholutsky, Thomas L. Griffiths
2023 A* conf
Diagnosis, Feedback, Adaptation: A Human-in-the-Loop Framework for Test-Time Policy Adaptation.
ICML
Andi Peng, Aviv Netanyahu, Mark K. Ho, Tianmin Shu, Andreea Bobu, Julie Shah, Pulkit Agrawal
2023 J jnl
Diagnosis, Feedback, Adaptation: A Human-in-the-Loop Framework for Test-Time Policy Adaptation.
CoRR
Andi Peng, Aviv Netanyahu, Mark K. Ho, Tianmin Shu, Andreea Bobu, Julie Shah, Pulkit Agrawal
2023 J jnl
Exploring the hierarchical structure of human plans via program generation.
CoRR
Carlos G. Correa, Sophia Sanborn, Mark K. Ho, Frederick Callaway, Nathaniel D. Daw, Thomas L. Griffiths
2023 J jnl
Humans decompose tasks by trading off utility and computational cost.
PLoS Comput. Biol.
Carlos G. Correa, Mark K. Ho, Frederick Callaway, Nathaniel D. Daw, Thomas L. Griffiths
2023 J jnl
Structurally guided task decomposition in spatial navigation tasks.
CoRR
Ruiqi He, Carlos G. Correa, Thomas L. Griffiths, Mark K. Ho
2022 J jnl
Cognitive Science as a Source of Forward and Inverse Models of Human Decisions for Robotics and Control.
Annu. Rev. Control. Robotics Auton. Syst.
Mark K. Ho, Thomas L. Griffiths
2022 A* conf
How to talk so AI will learn: Instructions, descriptions, and autonomy.
NeurIPS
Theodore R. Sumers, Robert D. Hawkins, Mark K. Ho, Tom Griffiths, Dylan Hadfield-Menell
2022 J jnl
How to talk so your robot will learn: Instructions, descriptions, and pragmatics.
CoRR
Theodore R. Sumers, Robert D. Hawkins, Mark K. Ho, Thomas L. Griffiths, Dylan Hadfield-Menell
2022 J jnl
Humans decompose tasks by trading off utility and computational cost.
CoRR
Carlos G. Correa, Mark K. Ho, Frederick Callaway, Nathaniel D. Daw, Thomas L. Griffiths
2022 J jnl
Linguistic communication as (inverse) reward design.
CoRR
Theodore R. Sumers, Robert D. Hawkins, Mark K. Ho, Thomas L. Griffiths, Dylan Hadfield-Menell
2022 J jnl
On Rate-Distortion Theory in Capacity-Limited Cognition & Reinforcement Learning.
CoRR
Dilip Arumugam, Mark K. Ho, Noah D. Goodman, Benjamin Van Roy
2022 A* conf
On the Expressivity of Markov Reward (Extended Abstract).
IJCAI
David Abel, Will Dabney, Anna Harutyunyan, Mark K. Ho, Michael L. Littman, Doina Precup, Satinder Singh
2021 J jnl
Cognitive science as a source of forward and inverse models of human decisions for robotics and control.
CoRR
Mark K. Ho, Thomas L. Griffiths
2021 J jnl
Control of mental representations in human planning.
CoRR
Mark K. Ho, David Abel, Carlos G. Correa, Michael L. Littman, Jonathan D. Cohen, Thomas L. Griffiths
2021 B conf
Extending rational models of communication from beliefs to actions.
CogSci
Theodore R. Sumers, Robert D. Hawkins, Mark K. Ho, Tom Griffiths
2021 J jnl
Extending rational models of communication from beliefs to actions.
CoRR
Theodore R. Sumers, Robert X. D. Hawkins, Mark K. Ho, Thomas L. Griffiths
2021 A* conf
Learning Rewards From Linguistic Feedback.
AAAI
Theodore R. Sumers, Mark K. Ho, Robert X. D. Hawkins, Karthik Narasimhan, Thomas L. Griffiths
2021 A* conf
On the Expressivity of Markov Reward.
NeurIPS
David Abel, Will Dabney, Anna Harutyunyan, Mark K. Ho, Michael L. Littman, Doina Precup, Satinder Singh
2021 J jnl
On the Expressivity of Markov Reward.
CoRR
David Abel, Will Dabney, Anna Harutyunyan, Mark K. Ho, Michael L. Littman, Doina Precup, Satinder Singh
2021 B conf
Specialization and selective social attention establishes the balance between individual and social learning.
CogSci
Charley M. Wu, Mark K. Ho, Benjamin Kahl, Christina Leuker, Björn Meder, Ralf H. J. M. Kurvers
2021 B conf
Using Machine Teaching to Investigate Human Assumptions when Teaching Reinforcement Learners.
CogSci
Yun-Shiuan Chuang, Xuezhou Zhang, Yuzhe Ma, Mark K. Ho, Joseph L. Austerweil, Jerry Zhu
2020 B conf
Cognition, Collectives, and Human Culture.
CogSci
Charley M. Wu, Natalia Vélez, Mark K. Ho, Robert L. Goldstone
2020 J jnl
Learning Rewards from Linguistic Feedback.
CoRR
Theodore R. Sumers, Mark K. Ho, Robert X. D. Hawkins, Karthik Narasimhan, Thomas L. Griffiths
2020 A* conf
People Do Not Just Plan, They Plan to Plan.
AAAI
Mark K. Ho, David Abel, Jonathan D. Cohen, Michael L. Littman, Thomas L. Griffiths
2020 B conf
Punishment: Incentive or Communication?
CogSci
Arunima Sarin, Mark K. Ho, Justin Martin, Fiery Cushman
2020 B conf
Resource-rational Task Decomposition to Minimize Planning Costs.
CogSci
Carlos G. Correa, Mark K. Ho, Frederick Callaway, Tom Griffiths
2020 J jnl
Resource-rational Task Decomposition to Minimize Planning Costs.
CoRR
Carlos G. Correa, Mark K. Ho, Fred Callaway, Thomas L. Griffiths
2020 B conf
Show or Tell? Demonstration is More Robust to Changes in Shared Perception than Explanation.
CogSci
Theodore R. Sumers, Mark K. Ho, Tom Griffiths
2020 J jnl
Show or Tell? Demonstration is More Robust to Changes in Shared Perception than Explanation.
CoRR
Theodore R. Sumers, Mark K. Ho, Thomas L. Griffiths
2020 A* conf
Teaching a Robot Tasks of Arbitrary Complexity via Human Feedback.
HRI
Guan Wang, Carl Trimbach, Jun Ki Lee, Mark K. Ho, Michael L. Littman
2020 J jnl
The Efficiency of Human Cognition Reflects Planned Information Processing.
CoRR
Mark K. Ho, David Abel, Jonathan D. Cohen, Michael L. Littman, Thomas L. Griffiths
2020 J jnl
Using Machine Teaching to Investigate Human Assumptions when Teaching Reinforcement Learners.
CoRR
Yun-Shiuan Chuang, Xuezhou Zhang, Yuzhe Ma, Mark K. Ho, Joseph L. Austerweil, Xiaojin Zhu
2019 B conf
Compositional subgoal representations.
CogSci
Carlos G. Correa, Frederick Callaway, Mark K. Ho, Tom Griffiths
2019 A* conf
On the Utility of Learning about Humans for Human-AI Coordination.
NeurIPS
Micah Carroll, Rohin Shah, Mark K. Ho, Tom Griffiths, Sanjit A. Seshia, Pieter Abbeel, Anca D. Dragan
2019 J jnl
On the Utility of Learning about Humans for Human-AI Coordination.
CoRR
Micah Carroll, Rohin Shah, Mark K. Ho, Thomas L. Griffiths, Sanjit A. Seshia, Pieter Abbeel, Anca D. Dragan
2019 B conf
The Computational Structure of Unintentional Meaning.
CogSci
Mark K. Ho, Joanna Korman, Tom Griffiths
2019 J jnl
The Computational Structure of Unintentional Meaning.
CoRR
Mark K. Ho, Joanna Korman, Thomas L. Griffiths
2018 B conf
Effectively Learning from Pedagogical Demonstrations.
CogSci
Mark K. Ho, Michael L. Littman, Fiery Cushman, Joseph L. Austerweil
2018 A* conf
Learning Task Specifications from Demonstrations.
NeurIPS
Marcell Vazquez-Chanlatte, Susmit Jha, Ashish Tiwari, Mark K. Ho, Sanjit A. Seshia
2017 A* conf
Interactive Learning from Policy-Dependent Human Feedback.
ICML
James MacGlashan, Mark K. Ho, Robert Tyler Loftin, Bei Peng, Guan Wang, David L. Roberts, Matthew E. Taylor, Michael L. Littman
2017 J jnl
Interactive Learning from Policy-Dependent Human Feedback.
CoRR
James MacGlashan, Mark K. Ho, Robert Tyler Loftin, Bei Peng, David L. Roberts, Matthew E. Taylor, Michael L. Littman
2017 B conf
Teaching by Intervention: Working Backwards, Undoing Mistakes, or Correcting Mistakes?
CogSci
Mark K. Ho, Michael L. Littman, Joseph L. Austerweil
2016 B conf
Coordinate to cooperate or compete: Abstract goals and joint intentions in social interaction.
CogSci
Max Kleiman-Weiner, Mark K. Ho, Joseph L. Austerweil, Michael L. Littman, Josh Tenenbaum
2016 B conf
Feature-based Joint Planning and Norm Learning in Collaborative Games.
CogSci
Mark K. Ho, James MacGlashan, Amy Greenwald, Michael L. Littman, Elizabeth Hilliard, Carl Trimbach, Stephen Brawner, Josh Tenenbaum, Max Kleiman-Weiner, Joseph L. Austerweil
2016 — conf
Showing versus doing: Teaching by demonstration.
NIPS
Mark K. Ho, Michael L. Littman, James MacGlashan, Fiery Cushman, Joseph L. Austerweil
2015 B conf
Teaching with Rewards and Punishments: Reinforcement or Communication?
CogSci
Mark K. Ho, Michael L. Littman, Fiery Cushman, Joseph L. Austerweil
2013 B conf
Working Memory and Abstract Representation in the Context of Culture.
CogSci
Mark K. Ho, Fiery Cushman