Gerald Tesauro

Publication Activity (10 Years)

Years Active: 1987-2023
Publications (10 Years): 49

Top Venues

CoRR

AAAI

NeurIPS

ICLR (Poster)

Publications

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)
Cameron Allen, Michael Katz, Tim Klinger, George Konidaris, Matthew Riemer, Gerald Tesauro
Efficient Black-Box Planning Using Macro-Actions with Focused Effects. IJCAI (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)
Keerthiram Murugesan, Mattia Atzeni, Pavan Kapanipathi, Pushkar Shukla, Sadhana Kumaravel, Gerald Tesauro, Kartik Talamadupula, Mrinmaya Sachan, Murray Campbell
Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselines. AAAI (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)
Keerthiram Murugesan, Mattia Atzeni, Pavan Kapanipathi, Pushkar Shukla, Sadhana Kumaravel, Gerald Tesauro, Kartik Talamadupula, Mrinmaya Sachan, Murray Campbell
Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselines. CoRR (2020)
Gang Wang, Songtao Lu, Georgios B. Giannakis, Gerald Tesauro, Jian Sun
Decentralized TD Tracking with Linear Function Approximation and its Finite-Time Analysis. NeurIPS (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)
Cameron Allen, Tim Klinger, George Konidaris, Matthew Riemer, Gerald Tesauro
Finding Macro-Actions with Disentangled Effects for Efficient Planning with the Goal-Count Heuristic. CoRR (2020)
Xiaoxiao Guo, Shiyu Chang, Mo Yu, Gerald Tesauro, Murray Campbell
Hybrid Reinforcement Learning with Expert State Sequences. CoRR (2019)
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)
Xiaoxiao Guo, Shiyu Chang, Mo Yu, Gerald Tesauro, Murray Campbell
Hybrid Reinforcement Learning with Expert State Sequences. AAAI (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)
Shuohang Wang, Mo Yu, Jing Jiang, Wei Zhang, Xiaoxiao Guo, Shiyu Chang, Zhiguo Wang, Tim Klinger, Gerald Tesauro, Murray Campbell
Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering. ICLR (Poster) (2018)
Ron Sun, David Silver, Gerald Tesauro, Guang-Bin Huang
Introduction to the special issue on deep reinforcement learning: An editorial. Neural Networks 107 (2018)
Xiaoxiao Guo, Hui Wu, Yu Cheng, Steven Rennie, Gerald Tesauro, Rogério Schmidt Feris
Dialog-based Interactive Image Retrieval. NeurIPS (2018)
Mo Yu, Xiaoxiao Guo, Jinfeng Yi, Shiyu Chang, Saloni Potdar, Yu Cheng, Gerald Tesauro, Haoyu Wang, Bowen Zhou
Diverse Few-Shot Text Classification with Multiple Metrics. CoRR (2018)
Mo Yu, Xiaoxiao Guo, Jinfeng Yi, Shiyu Chang, Saloni Potdar, Yu Cheng, Gerald Tesauro, Haoyu Wang, Bowen Zhou
Diverse Few-Shot Text Classification with Multiple Metrics. NAACL-HLT (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)
Iulian Vlad Serban, Tim Klinger, Gerald Tesauro, Kartik Talamadupula, Bowen Zhou, Yoshua Bengio, Aaron C. Courville
Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation. AAAI (2017)
Mohan Sridharan, Gerald Tesauro, James A. Hendler
Cognitive Computing. IEEE Intell. Syst. 32 (4) (2017)
Miao Liu, Marlos C. Machado, Gerald Tesauro, Murray Campbell
The Eigenoption-Critic Framework. CoRR (2017)
Mo Yu, Xiaoxiao Guo, Jinfeng Yi, Shiyu Chang, Saloni Potdar, Gerald Tesauro, Haoyu Wang, Bowen Zhou
Robust Task Clustering for Deep Many-Task 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)
Shuohang Wang, Mo Yu, Xiaoxiao Guo, Zhiguo Wang, Tim Klinger, Wei Zhang, Shiyu Chang, Gerald Tesauro, Bowen Zhou, Jing Jiang
: Reinforced Reader-Ranker for Open-Domain Question Answering. CoRR (2017)
Shuohang Wang, Mo Yu, Jing Jiang, Wei Zhang, Xiaoxiao Guo, Shiyu Chang, Zhiguo Wang, Tim Klinger, Gerald Tesauro, Murray Campbell
Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering. CoRR (2017)
Ruben Rodriguez Torrado, Jesus Rios, Gerald Tesauro
Optimal Sequential Drilling for Hydrocarbon Field Development Planning. AAAI (2017)
Sarath Chandar, Sungjin Ahn, Hugo Larochelle, Pascal Vincent, Gerald Tesauro, Yoshua Bengio
Hierarchical Memory Networks. CoRR (2016)
Ashish Sabharwal, Horst Samulowitz, Gerald Tesauro
Selecting Near-Optimal Learners via Incremental Data Allocation. AAAI (2016)
Iulian Vlad Serban, Tim Klinger, Gerald Tesauro, Kartik Talamadupula, Bowen Zhou, Yoshua Bengio, Aaron C. Courville
Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation. CoRR (2016)
Ashish Sabharwal, Horst Samulowitz, Gerald Tesauro
Selecting Near-Optimal Learners via Incremental Data Allocation. CoRR (2016)
Alain Biem, Maria Butrico, Mark Feblowitz, Tim Klinger, Yuri Malitsky, Kenney Ng, Adam Perer, Chandra Reddy, Anton Riabov, Horst Samulowitz, Daby M. Sow, Gerald Tesauro, Deepak S. Turaga
Towards Cognitive Automation of Data Science. AAAI (2015)
Stefano V. Albrecht, André da Motta Salles Barreto, Darius Braziunas, David L. Buckeridge, Heriberto Cuayáhuitl, Nina Dethlefs, Markus Endres, Amir-massoud Farahmand, Mark Fox, Lutz Frommberger, Sam Ganzfried, Yolanda Gil, Sébastien Guillet, Lawrence E. Hunter, Arnav Jhala, Kristian Kersting, George Dimitri Konidaris, Freddy Lécué, Sheila A. McIlraith, Sriraam Natarajan, Zeinab Noorian, David Poole, Rémi Ronfard, Alessandro Saffiotti, Arash Shaban-Nejad, Biplav Srivastava, Gerald Tesauro, Rosario Uceda-Sosa, Guy Van den Broeck, Martijn van Otterlo, Byron C. Wallace, Paul Weng, Jenna Wiens, Jie Zhang
Reports of the AAAI 2014 Conference Workshops. AI Mag. 36 (1) (2015)
Kareem Amin, Satyen Kale, Gerald Tesauro, Deepak S. Turaga
Budgeted Prediction with Expert Advice. AAAI (2015)
Gerald Tesauro, David Gondek, Jonathan Lenchner, James Fan, John M. Prager
Analysis of Watson's Strategies for Playing Jeopardy! CoRR (2014)
Gerald Tesauro, V. T. Rajan, Richard B. Segal
Bayesian Inference in Monte-Carlo Tree Search CoRR (2012)
Joseph P. Bigus, Ching-Hua Chen-Ritzo, Keith Hermiz, Gerald Tesauro, Robert Sorrentino
Applying a framework for healthcare incentives simulation. WSC (2012)
Craig Boutilier, Rajarshi Das, Jeffrey O. Kephart, Gerald Tesauro, William E. Walsh
Cooperative Negotiation in Autonomic Systems using Incremental Utility Elicitation CoRR (2012)
Janusz Marecki, Gerald Tesauro, Richard B. Segal
Playing repeated Stackelberg games with unknown opponents. AAMAS (2012)
Gerald Tesauro, V. T. Rajan, Richard B. Segal
Bayesian Inference in Monte-Carlo Tree Search. UAI (2010)
David Silver, Gerald Tesauro
Monte-Carlo simulation balancing. ICML (2009)
Irina Rish, Gerald Tesauro
Active Collaborative Prediction with Maximum Margin Matrix Factorization. ISAIM (2008)
Rajarshi Das, Jeffrey O. Kephart, Charles Lefurgy, Gerald Tesauro, David W. Levine, Hoi Y. Chan
Autonomic multi-agent management of power and performance in data centers. AAMAS (Industry Track) (2008)
Gerald Tesauro
Reinforcement Learning in Autonomic Computing: A Manifesto and Case Studies. IEEE Internet Comput. 11 (1) (2007)
Jeffrey O. Kephart, Hoi Y. Chan, Rajarshi Das, David W. Levine, Gerald Tesauro, Freeman L. Rawson III, Charles Lefurgy
Coordinating Multiple Autonomic Managers to Achieve Specified Power-Performance Tradeoffs. ICAC (2007)
Gerald Tesauro, Rajarshi Das, Hoi Y. Chan, Jeffrey O. Kephart, David Levine, Freeman L. Rawson III, Charles Lefurgy
Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning. NIPS (2007)
Gerald Tesauro, Nicholas K. Jong, Rajarshi Das, Mohamed N. Bennani
On the use of hybrid reinforcement learning for autonomic resource allocation. Clust. Comput. 10 (3) (2007)
Irina Rish, Gerald Tesauro
Estimating End-to-End Performance by Collaborative Prediction with Active Sampling. Integrated Network Management (2007)
Kilian Q. Weinberger, Gerald Tesauro
Metric Learning for Kernel Regression. AISTATS (2007)
Gerald Tesauro, Nicholas K. Jong, Rajarshi Das, Mohamed N. Bennani
Improvement of Systems Management Policies Using Hybrid Reinforcement Learning. ECML (2006)
Gerald Tesauro, Nicholas K. Jong, Rajarshi Das, Mohamed N. Bennani
A Hybrid Reinforcement Learning Approach to Autonomic Resource Allocation. ICAC (2006)
Gerald Tesauro
Online Resource Allocation Using Decompositional Reinforcement Learning. AAAI (2005)
Gerald Tesauro, Rajarshi Das, William E. Walsh, Jeffrey O. Kephart
Utility-Function-Driven Resource Allocation in Autonomic Systems. ICAC (2005)
Relu Patrascu, Craig Boutilier, Rajarshi Das, Jeffrey O. Kephart, Gerald Tesauro, William E. Walsh
New Approaches to Optimization and Utility Elicitation in Autonomic Computing. AAAI (2005)
Gerald Tesauro, David M. Chess, William E. Walsh, Rajarshi Das, Alla Segal, Ian Whalley, Jeffrey O. Kephart, Steve R. White
A Multi-Agent Systems Approach to Autonomic Computing. AAMAS (2004)
William E. Walsh, Gerald Tesauro, Jeffrey O. Kephart, Rajarshi Das
Utility Functions in Autonomic Systems. ICAC (2004)
Cuihong Li, Gerald Tesauro
A strategic decision model for multi-attribute bilateral negotiation with alternating. EC (2003)
James E. Hanson, Gerald Tesauro, Jeffrey O. Kephart, E. C. Snibl
Multi-agent implementation of asymmetric protocol for bilateral negotiations. EC (2003)
Craig Boutilier, Rajarshi Das, Jeffrey O. Kephart, Gerald Tesauro, William E. Walsh
Cooperative Negotiation in Autonomic Systems using Incremental Utility Elicitation. UAI (2003)
Gerald Tesauro
Extending Q-Learning to General Adaptive Multi-Agent Systems. NIPS (2003)
Gerald Tesauro
Programming backgammon using self-teaching neural nets. Artif. Intell. 134 (1-2) (2002)
Gerald Tesauro, Jonathan Bredin
Strategic sequential bidding in auctions using dynamic programming. AAMAS (2002)
Gerald Tesauro, Jeffrey O. Kephart
Pricing in Agent Economies Using Multi-Agent Q-Learning. Auton. Agents Multi Agent Syst. 5 (3) (2002)
Gerald Tesauro
Pricing in Agent Economies Using Neural Networks and Multi-agent Q-Learning. Sequence Learning (2001)
Gerald Tesauro, Rajarshi Das
High-performance bidding agents for the continuous double auction. EC (2001)
Rajarshi Das, James E. Hanson, Jeffrey O. Kephart, Gerald Tesauro
Agent-Human Interactions in the Continuous Double Auction. IJCAI (2001)
Gerald Tesauro, Jeffrey O. Kephart
Foresight-based pricing algorithms in agent economies. Decis. Support Syst. 28 (1-2) (2000)
Manu Sridharan, Gerald Tesauro
Multi-agent Q-learning and Regression Trees for Automated Pricing Decisions. ICML (2000)
Manu Sridharan, Gerald Tesauro
Multi-Agent Q-Learning and Regression Trees for Automated Pricing Decisions. ICMAS (2000)
Jeffrey O. Kephart, Gerald Tesauro
Pseudo-convergent Q-Learning by Competitive Pricebots. ICML (2000)
Amy Greenwald, Jeffrey O. Kephart, Gerald Tesauro
Strategic pricebot dynamics. EC (1999)
Gerald Tesauro, Jeffrey O. Kephart
Foresight-based pricing algorithms in an economy of software agents. ICE (1998)
Gerald Tesauro
Comments on "Co-Evolution in the Successful Learning of Backgammon Strategy". Mach. Learn. 32 (3) (1998)
Gerald Tesauro, Gregory R. Galperin
On-line Policy Improvement using Monte-Carlo Search. NIPS (1996)
Gerald Tesauro
Temporal Difference Learning and TD-Gammon. J. Int. Comput. Games Assoc. 18 (2) (1995)
Gerald Tesauro
Temporal Difference Learning and TD-Gammon. Commun. ACM 38 (3) (1995)
Jeffrey O. Kephart, Gregory B. Sorkin, William C. Arnold, David M. Chess, Gerald Tesauro, Steve R. White
Biologically Inspired Defenses Against Computer Viruses. IJCAI (1) (1995)
Gerald Tesauro
TD-Gammon, a Self-Teaching Backgammon Program, Achieves Master-Level Play. Neural Comput. 6 (2) (1994)
Gerald Tesauro
Temporal Difference Learning of Backgammon Strategy. ML (1992)
Gerald Tesauro
Practical Issues in Temporal Difference Learning. Mach. Learn. 8 (1992)
David A. Cohn, Gerald Tesauro
How Tight Are the Vapnik-Chervonenkis Bounds? Neural Comput. 4 (2) (1992)
Gerald Tesauro
Practical Issues in Temporal Difference Learning. NIPS (1991)

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Publication Activity (10 Years)

Top Topics

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Gerald Tesauro