Scaling Laws for Pre-training Agents and World Models
Tim Pearce, Tabish Rashid, Dave Bignell, Raluca Stevenson, Sam Devlin, Katja Hofmann
November 2024
Katja Hofmann
Senior Principal Research Manager and lead of the Microsoft Research Game Intelligence team
Publications
Publications by Year
-
Learning Safety Constraints from Demonstrations with Unknown Rewards
David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
International Conference on Artificial Intelligence and Statistics | April 2024
Toward Human-AI Alignment in Large-Scale Multi-Player Games
Sugandha Sharma, Guy Davidson, Khimya Khetarpal, Anssi Kanervisto, Udit Arora, Katja Hofmann, Ida Momennejad
arXiv:2402.03575 | February 2024
Published by Microsoft
Transformer Neural Autoregressive Flows
Massimiliano Patacchiola, Aliaksandra Shysheya, Katja Hofmann, Richard E Turner
January 2024
-
Comparing the Efficacy of Fine-Tuning and Meta-Learning for Few-Shot Policy Imitation
Massimiliano Patacchiola, Mingfei Sun, Katja Hofmann, Richard E Turner
Conference on Lifelong Learning Agents | November 2023
Imitating Human Behaviour with Diffusion Models
Tim Pearce, Tabish Rashid, Anssi Kanervisto, Dave Bignell, Mingfei Sun, Raluca Stevenson, Sergio Valcarcel Macua, Shanzheng Tan, Ida Momennejad, Katja Hofmann, Sam Devlin
ICLR 2023 | May 2023
Trust Region Bounds for Decentralized PPO Under Non-stationarity
Mingfei Sun, Sam Devlin, Jacob Beck, Katja Hofmann, Shimon Whiteson
International Conference on Autonomous Agents and Multiagent Systems (AAMAS) | May 2023
Best Paper Award
Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games
Stephanie Milani, Arthur Juliani, Ida Momennejad, Raluca Stevenson, Jaroslaw Rzepecki, Alison Shaw, Gavin Costello, Fei Fang, Sam Devlin, Katja Hofmann
CHI | April 2023
-
Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification
Massimiliano Patacchiola, John F Bronskill, Aliaksandra Shysheya, Katja Hofmann, Sebastian Nowozin, Richard E Turner
NeurIPS 2022 | November 2022
Uni[MASK]: Unified Inference in Sequential Decision Problems
Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, Dave Bignell, Stephanie Milani, Katja Hofmann, Matthew Hausknecht, Anca Dragan, Sam Devlin
2022 Neural Information Processing Systems | November 2022
Interactively Learning Preference Constraints in Linear Bandits
David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
ICML 2022 | June 2022
How Humans Perceive Human-like Behavior in Video Game Navigation
Evelyn Zuniga, Stephanie Milani, Guy Leroy, Jaroslaw Rzepecki, Raluca Stevenson, Ida Momennejad, Dave Bignell, Mingfei Sun, Alison Shaw, Gavin Costello, Mikhail Jacob, Sam Devlin, Katja Hofmann
CHI 2022 | April 2022
Deterministic and Discriminative Imitation (D2-Imitation): Revisiting Adversarial Imitation for Sample Efficiency
Mingfei Sun, Sam Devlin, Katja Hofmann, Shimon Whiteson
AAAI 2022 | February 2022
SpatialSim: Recognizing Spatial Configurations of Objects with Graph Neural Networks
Laetitia Teodorescu, Katja Hofmann, Pierre-Yves Oudeyer1
Frontiers in Artificial Intelligence | January 2022, Vol 4
-
Grounding Spatio-Temporal Language with Transformers
Tristan Karch, Laetitia Teodorescu, Katja Hofmann, Clément Moulin-Frier, Pierre-Yves Oudeyer
NeurIPS 2021 | December 2021
Memory Efficient Meta-Learning with Large Images
John Bronskill, Daniela Massiceti, Massimiliano Patacchiola, Katja Hofmann, Richard Turner
NeurIPS 2021 | December 2021
Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors
Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Ed Cutrell, Matthew Tobias Harris, Katja Hofmann
International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS) | October 2021
ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition
Daniela Massiceti, Luisa Zintgraf, John Bronskill, Lida Theodorou, Matthew Tobias Harris, Ed Cutrell, Cecily Morrison, Katja Hofmann, Simone Stumpf
ICCV 2021 | October 2021
Strategically Efficient Exploration in Competitive Multiagent Reinforcement Learning
Robert Loftin, Aadirupa Saha, Sam Devlin, Katja Hofmann
Conference on Uncertainty in Artificial Intelligence (UAI) 2021 | July 2021
Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation
Sam Devlin, Raluca Stevenson, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann
2021 International Conference on Machine Learning | July 2021
Source code available at: https://github.com/microsoft/NTT
Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning
Luisa Zintgraf, Leo Feng, Cong Lu, Maximilian Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson
2021 International Conference on Machine Learning | July 2021
TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL
Clément Romac, Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer
2021 International Conference on Machine Learning | July 2021
Deep Interactive Bayesian Reinforcement Learning via Meta-Learning
Luisa Zintgraf, Sam Devlin, Kamil Ciosek, Shimon Whiteson, Katja Hofmann
20th International Conference on Autonomous Agents and Multiagent Systems | May 2021
Evaluating the Robustness of Collaborative Agents
Paul Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca Dragan, Rohin Shah
20th International Conference on Autonomous Agents and Multiagent Systems | May 2021
-
“It’s Unwieldy and It Takes a Lot of Time.” Challenges and Opportunities for Creating Agents in Commercial Games
Mikhail Jacob, Sam Devlin, Katja Hofmann
16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment | October 2020
AIIDE 2020 BEST PAPER AWARD
Best paper award winner.
Variational Integrator Networks for Physically Meaningful Embeddings
Steindór Sæmundsson, Alexander Terenin, Katja Hofmann, Marc Peter Deisenroth
Twenty-Third International Conference on Artificial Intelligence and Statistics (AISTATS) | June 2020
Combining No-regret and Q-learning
Ian A. Kash, Michael Sullins, Katja Hofmann
2020 Adaptive Agents and Multi-Agents Systems | May 2020
A Novel Individually Rational Objective In Multi-Agent Multi-Armed Bandit: Algorithms and Regret Bounds
Aristide Tossou, Christos Dimitrakakis, Jaroslaw Rzepecki, Katja Hofmann
International Conference on Autonomous Agents and Multiagent Systems (AAMAS) | May 2020
AMRL: Aggregated Memory For Reinforcement Learning
Jacob Beck, Kamil Ciosek, Sam Devlin, Sebastian Tschiatschek, Cheng Zhang, Katja Hofmann
Eighth International Conference on Learning Representations (ICLR) | April 2020
Conservative Uncertainty Estimation By Fitting Prior Networks
Kamil Ciosek, Vincent Fortuin, Ryota Tomioka, Katja Hofmann, Richard Turner
Eighth International Conference on Learning Representations (ICLR) | April 2020
VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning
Luisa Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson
Eighth International Conference on Learning Representations (ICLR) | April 2020
Automatic Curriculum Learning for Deep RL: A Short Survey
Rémy Portelas, Cédric Colas, Lilian Weng, Katja Hofmann, Pierre-Yves Oudeyer
International Joint Conference on Artificial Intelligence | March 2020
-
Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck
Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann
Thirty-third Conference on Neural Information Processing Systems (NeurIPS) | December 2019
Better Exploration with Optimistic Actor-Critic
Kamil Ciosek, Quan Vuong, Robert Loftin, Katja Hofmann
33rd Conference on Neural Information Processing Systems (NeurIPS) | December 2019
Reinforcement Learning: Past, Present, and Future Perspectives
Thirty-third Conference on Neural Information Processing Systems (NeurIPS) | December 2019
Tutorial
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning
David Janz, Jiri Hron, Przemysław Mazur, Katja Hofmann, Jose Miguel Hernandez Lobato, Sebastian Tschiatschek
Thirty-third Conference on Neural Information Processing Systems (NeurIPS) | December 2019
The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors
William H Guss, Cayden Codel, Katja Hofmann, Brandon Houghton, Noboru Sean Kuno, Stephanie Milani, Sharada Mohanty, Diego Perez Liebana, Ruslan Salakhutdinov, Nicholay Topin, Manuela Veloso, Philip Wang
Thirty-third Conference on Neural Information Processing Systems (NeurIPS) Competition track | December 2019
Minecraft as AI Playground and Laboratory
Proceedings of the Annual Symposium on Computer-Human Interaction in Play (ChiPlay) | November 2019
Opening keynote (extended abstract)
Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments
Rémy Portelas, Pierre-Yves Oudeyer, Cédric Colas, Katja Hofmann
Third Conference on Robot Learning (CoRL) | October 2019
MazeExplorer: A Customisable 3D Benchmark for Assessing Generalisation in Reinforcement Learning
Luke Harries, Sebastian Lee, Jaroslaw Rzepecki, Katja Hofmann, Sam Devlin
IEEE Conference on Games | August 2019
Win or Learn Fast Proximal Policy Optimisation
Dino Ratcliffe, Katja Hofmann, Sam Devlin
IEEE Conference on Games | August 2019
Fast Context Adaptation via Meta-Learning
Luisa Zintgraf, Kyriacos Shiarlis, Vitaly Kurin, Katja Hofmann, Shimon Whiteson
Thirty-sixth International Conference on Machine Learning (ICML) | June 2019
The Multi-Agent Reinforcement Learning in MalmÖ (MARLÖ) Competition
Diego Perez-Liebana, Katja Hofmann, Sharada Prasanna Mohanty, Noboru Sean Kuno, Andre Kramer, Sam Devlin, Raluca D. Gaina, Daniel Ionita
1901.08129 | January 2019
Published by Arxiv
-
How Players Speak to an Intelligent Game Character Using Natural Language Messages
Fraser Allison, Ewa Luger, Katja Hofmann
Transactions of the Digital Games Research Association | December 2018, Vol 4(2): pp. 1-49
Combining No-regret and Q-learning (2018)
Ian Kash, Katja Hofmann
The 14th European Workshop on Reinforcement Learning (EWRL 2018) | October 2018
Also presented at the AAAI-19 workshop on Reinforcement Learning in Games.
Learning good policies from suboptimal demonstrations
Yuxiang Li, Ian Kash, Katja Hofmann
The 14th European Workshop on Reinforcement Learning (EWRL 2018) | October 2018
Advancements in Dueling Bandits
Yanan Sui, Masrour Zoghi, Katja Hofmann, Yisong Yue
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence | July 2018
Depth and nonlinearity induce implicit exploration for RL
Justas Dauparas, Ryota Tomioka, Katja Hofmann
ICML workshop on Exploration in RL | July 2018
Meta Reinforcement Learning with Latent Variable Gaussian Processes
Steindór Sæmundsson, Katja Hofmann, Marc Peter Deisenroth
Conference on Uncertainty in Artificial Intelligence (UAI) | May 2018
Variational Inference for Data-Efficient Model Learning in POMDPs
Sebastian Tschiatschek, Kai Arulkumaran, Jan Stuehmer, Katja Hofmann
MSR-TR-2018-15 | May 2018
Published by Microsoft
Cross Domain Regularization for Neural Ranking Models Using Adversarial Learning
Daniel Cohen, Bhaskar Mitra, Katja Hofmann, W. Bruce Croft
Proceedings of the 41st international ACM SIGIR conference on Research & development in information retrieval | May 2018
Best Short Research Paper
-
A New AI Evaluation Cosmos: Ready to Play the Game?
José Hérnandez-Orallo, Marco Baroni, Jordi Bieger, Nader Chmait, David L. Dowe, Katja Hofmann, Fernando Martínez-Plumed, Claes Strannegård, Kristinn R. Thórisson
AI Magazine | September 2017, Vol 38
A Deep Learning Approach for Joint Video Frame and Reward Prediction in Atari Games
Felix Leibfried, Nate Kushman, Katja Hofmann
ICML workshop on Principled Approaches to Deep Learning | August 2017
Asynchronous Data Aggregation for Training End to End Visual Control Networks
Mathew Monfort, Matthew Johnson, Aude Oliva, Katja Hofmann
AAMAS '17 Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems | May 2017
Spontaneous Interactions with a Virtually Embodied Intelligent Assistant in Minecraft
Fraser Allison, Ewa Luger, Katja Hofmann
CHI EA '17 Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems | May 2017
The Atari Grand Challenge Dataset
Vitaly Kurin, Sebastian Nowozin, Katja Hofmann, Lucas Beyer, Bastian Leibe
MSR-TR-2017-61 | May 2017
Published by Microsoft
-
Memory Lens – How Much Memory Does an Agent Use?
Christoph Dann, Katja Hofmann, Sebastian Nowozin
The 13th European Workshop on Reinforcement Learning (EWRL) 2016 | December 2016
Also presented at the Interpretable ML for Complex Systems Workshop at NeurIPS 2016
Decoding multitask DQN in the world of Minecraft
Lydia T. Liu, Urun Dogan, Katja Hofmann
The 13th European Workshop on Reinforcement Learning (EWRL) 2016 | December 2016
Also presented at the 11th Women in Machine Learning Workshop and the Deep Reinforcement Learning Workshop at NeurIPS 2016.
Experimental and Causal View on Information Integration in Autonomous Agents
Philipp Geiger, Katja Hofmann, Bernhard Schölkopf
6th International Workshop on Combinations of Intelligent Methods and Applications | August 2016
6th International Workshop on Combinations of Intelligent Methods and Applications
The Malmo Platform for Artificial Intelligence Experimentation
Matthew Johnson, Katja Hofmann, Tm Hutton, David Bignell, Katja Hofmann
25th International Joint Conference on Artificial Intelligence (IJCAI-16) | July 2016
Online Evaluation for Information Retrieval
Katja Hofmann, Lihong Li, Filip Radlinski
Foundations and Trends® in Information Retrieval | June 2016, Vol 10: pp. 1-117
Towards Conversational Recommender Systems
Konstantina Christakopoulou, Filip Radlinski, Katja Hofmann
22nd ACM SigKDD Conference on Knowledge Discovery and Data Mining | June 2016
Collective Noise Contrastive Estimation for Policy Transfer Learning
Weinan Zhang, Ulrich Paquet, Katja Hofmann
Thirtieth AAAI Conference on Artificial Intelligence (AAAI 2016) | February 2016
-
Predicting Search Satisfaction Metrics with Interleaved Comparisons
Anne Schuth, Katja Hofmann, Filip Radlinski
Proceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR) | August 2015
Proceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR)
Contextual Dueling Bandits
Miro Dudík, Katja Hofmann, Robert E. Schapire, Aleksandrs Slivkins, Masrour Zoghi
Proceedings of The 28th Conference on Learning Theory (COLT) | July 2015
Proceedings of The 28th Conference on Learning Theory (COLT)
Online Learning to Rank: Absolute vs. Relative
Yiwei Chen, Katja Hofmann
Proceedings of the 24th international conference on World Wide Web (WWW) | May 2015
-
An Eye-tracking Study of User Interactions with Query Auto Completion
Katja Hofmann, Bhaskar Mitra, Filip Radlinski, Milad Shokouhi
Proceedings of the 23rd ACM International Conference on Information and Knowledge Management (CIKM) | November 2014
On User Interactions with Query Auto-Completion
Bhaskar Mitra, Milad Shokouhi, Filip Radlinski, Katja Hofmann
Proceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR) | July 2014
Effects of Position Bias on Click-Based Recommender Evaluation
Katja Hofmann, Anne Schuth, Alejandro Bellogin, Maarten de Rijke
36th European Conference on Information Retrieval (ECIR'14) | January 2014
-
Lerot: An Online Learning to Rank Framework
Anne Schuth, Katja Hofmann, Shimon Whiteson, Maarten de Rijke
Living Lab'13: Workshop on Living Labs for Information Retrieval Evaluation | January 2013
Living Lab'13: Workshop on Living Labs for Information Retrieval Evaluation
Publications by Research Area
-
Scaling Laws for Pre-training Agents and World Models
Tim Pearce, Tabish Rashid, Dave Bignell, Raluca Stevenson, Sam Devlin, Katja Hofmann
November 2024
Learning Safety Constraints from Demonstrations with Unknown Rewards
David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
International Conference on Artificial Intelligence and Statistics | April 2024
Toward Human-AI Alignment in Large-Scale Multi-Player Games
Sugandha Sharma, Guy Davidson, Khimya Khetarpal, Anssi Kanervisto, Udit Arora, Katja Hofmann, Ida Momennejad
arXiv:2402.03575 | February 2024
Published by Microsoft
Transformer Neural Autoregressive Flows
Massimiliano Patacchiola, Aliaksandra Shysheya, Katja Hofmann, Richard E Turner
January 2024
Comparing the Efficacy of Fine-Tuning and Meta-Learning for Few-Shot Policy Imitation
Massimiliano Patacchiola, Mingfei Sun, Katja Hofmann, Richard E Turner
Conference on Lifelong Learning Agents | November 2023
Trust Region Bounds for Decentralized PPO Under Non-stationarity
Mingfei Sun, Sam Devlin, Jacob Beck, Katja Hofmann, Shimon Whiteson
International Conference on Autonomous Agents and Multiagent Systems (AAMAS) | May 2023
Best Paper Award
Imitating Human Behaviour with Diffusion Models
Tim Pearce, Tabish Rashid, Anssi Kanervisto, Dave Bignell, Mingfei Sun, Raluca Stevenson, Sergio Valcarcel Macua, Shanzheng Tan, Ida Momennejad, Katja Hofmann, Sam Devlin
ICLR 2023 | May 2023
Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games
Stephanie Milani, Arthur Juliani, Ida Momennejad, Raluca Stevenson, Jaroslaw Rzepecki, Alison Shaw, Gavin Costello, Fei Fang, Sam Devlin, Katja Hofmann
CHI | April 2023
Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification
Massimiliano Patacchiola, John F Bronskill, Aliaksandra Shysheya, Katja Hofmann, Sebastian Nowozin, Richard E Turner
NeurIPS 2022 | November 2022
Uni[MASK]: Unified Inference in Sequential Decision Problems
Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, Dave Bignell, Stephanie Milani, Katja Hofmann, Matthew Hausknecht, Anca Dragan, Sam Devlin
2022 Neural Information Processing Systems | November 2022
Interactively Learning Preference Constraints in Linear Bandits
David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
ICML 2022 | June 2022
Deterministic and Discriminative Imitation (D2-Imitation): Revisiting Adversarial Imitation for Sample Efficiency
Mingfei Sun, Sam Devlin, Katja Hofmann, Shimon Whiteson
AAAI 2022 | February 2022
SpatialSim: Recognizing Spatial Configurations of Objects with Graph Neural Networks
Laetitia Teodorescu, Katja Hofmann, Pierre-Yves Oudeyer1
Frontiers in Artificial Intelligence | January 2022, Vol 4
Grounding Spatio-Temporal Language with Transformers
Tristan Karch, Laetitia Teodorescu, Katja Hofmann, Clément Moulin-Frier, Pierre-Yves Oudeyer
NeurIPS 2021 | December 2021
Memory Efficient Meta-Learning with Large Images
John Bronskill, Daniela Massiceti, Massimiliano Patacchiola, Katja Hofmann, Richard Turner
NeurIPS 2021 | December 2021
ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition
Daniela Massiceti, Luisa Zintgraf, John Bronskill, Lida Theodorou, Matthew Tobias Harris, Ed Cutrell, Cecily Morrison, Katja Hofmann, Simone Stumpf
ICCV 2021 | October 2021
Strategically Efficient Exploration in Competitive Multiagent Reinforcement Learning
Robert Loftin, Aadirupa Saha, Sam Devlin, Katja Hofmann
Conference on Uncertainty in Artificial Intelligence (UAI) 2021 | July 2021
Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation
Sam Devlin, Raluca Stevenson, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann
2021 International Conference on Machine Learning | July 2021
Source code available at: https://github.com/microsoft/NTT
TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL
Clément Romac, Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer
2021 International Conference on Machine Learning | July 2021
Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning
Luisa Zintgraf, Leo Feng, Cong Lu, Maximilian Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson
2021 International Conference on Machine Learning | July 2021
Deep Interactive Bayesian Reinforcement Learning via Meta-Learning
Luisa Zintgraf, Sam Devlin, Kamil Ciosek, Shimon Whiteson, Katja Hofmann
20th International Conference on Autonomous Agents and Multiagent Systems | May 2021
Evaluating the Robustness of Collaborative Agents
Paul Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca Dragan, Rohin Shah
20th International Conference on Autonomous Agents and Multiagent Systems | May 2021
“It’s Unwieldy and It Takes a Lot of Time.” Challenges and Opportunities for Creating Agents in Commercial Games
Mikhail Jacob, Sam Devlin, Katja Hofmann
16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment | October 2020
AIIDE 2020 BEST PAPER AWARD
Best paper award winner.
Variational Integrator Networks for Physically Meaningful Embeddings
Steindór Sæmundsson, Alexander Terenin, Katja Hofmann, Marc Peter Deisenroth
Twenty-Third International Conference on Artificial Intelligence and Statistics (AISTATS) | June 2020
Combining No-regret and Q-learning
Ian A. Kash, Michael Sullins, Katja Hofmann
2020 Adaptive Agents and Multi-Agents Systems | May 2020
A Novel Individually Rational Objective In Multi-Agent Multi-Armed Bandit: Algorithms and Regret Bounds
Aristide Tossou, Christos Dimitrakakis, Jaroslaw Rzepecki, Katja Hofmann
International Conference on Autonomous Agents and Multiagent Systems (AAMAS) | May 2020
VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning
Luisa Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson
Eighth International Conference on Learning Representations (ICLR) | April 2020
Conservative Uncertainty Estimation By Fitting Prior Networks
Kamil Ciosek, Vincent Fortuin, Ryota Tomioka, Katja Hofmann, Richard Turner
Eighth International Conference on Learning Representations (ICLR) | April 2020
AMRL: Aggregated Memory For Reinforcement Learning
Jacob Beck, Kamil Ciosek, Sam Devlin, Sebastian Tschiatschek, Cheng Zhang, Katja Hofmann
Eighth International Conference on Learning Representations (ICLR) | April 2020
Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck
Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann
Thirty-third Conference on Neural Information Processing Systems (NeurIPS) | December 2019
Better Exploration with Optimistic Actor-Critic
Kamil Ciosek, Quan Vuong, Robert Loftin, Katja Hofmann
33rd Conference on Neural Information Processing Systems (NeurIPS) | December 2019
Reinforcement Learning: Past, Present, and Future Perspectives
Thirty-third Conference on Neural Information Processing Systems (NeurIPS) | December 2019
Tutorial
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning
David Janz, Jiri Hron, Przemysław Mazur, Katja Hofmann, Jose Miguel Hernandez Lobato, Sebastian Tschiatschek
Thirty-third Conference on Neural Information Processing Systems (NeurIPS) | December 2019
The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors
William H Guss, Cayden Codel, Katja Hofmann, Brandon Houghton, Noboru Sean Kuno, Stephanie Milani, Sharada Mohanty, Diego Perez Liebana, Ruslan Salakhutdinov, Nicholay Topin, Manuela Veloso, Philip Wang
Thirty-third Conference on Neural Information Processing Systems (NeurIPS) Competition track | December 2019
Minecraft as AI Playground and Laboratory
Proceedings of the Annual Symposium on Computer-Human Interaction in Play (ChiPlay) | November 2019
Opening keynote (extended abstract)
Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments
Rémy Portelas, Pierre-Yves Oudeyer, Cédric Colas, Katja Hofmann
Third Conference on Robot Learning (CoRL) | October 2019
MazeExplorer: A Customisable 3D Benchmark for Assessing Generalisation in Reinforcement Learning
Luke Harries, Sebastian Lee, Jaroslaw Rzepecki, Katja Hofmann, Sam Devlin
IEEE Conference on Games | August 2019
Win or Learn Fast Proximal Policy Optimisation
Dino Ratcliffe, Katja Hofmann, Sam Devlin
IEEE Conference on Games | August 2019
Fast Context Adaptation via Meta-Learning
Luisa Zintgraf, Kyriacos Shiarlis, Vitaly Kurin, Katja Hofmann, Shimon Whiteson
Thirty-sixth International Conference on Machine Learning (ICML) | June 2019
The Multi-Agent Reinforcement Learning in MalmÖ (MARLÖ) Competition
Diego Perez-Liebana, Katja Hofmann, Sharada Prasanna Mohanty, Noboru Sean Kuno, Andre Kramer, Sam Devlin, Raluca D. Gaina, Daniel Ionita
1901.08129 | January 2019
Published by Arxiv
How Players Speak to an Intelligent Game Character Using Natural Language Messages
Fraser Allison, Ewa Luger, Katja Hofmann
Transactions of the Digital Games Research Association | December 2018, Vol 4(2): pp. 1-49
Combining No-regret and Q-learning (2018)
Ian Kash, Katja Hofmann
The 14th European Workshop on Reinforcement Learning (EWRL 2018) | October 2018
Also presented at the AAAI-19 workshop on Reinforcement Learning in Games.
Learning good policies from suboptimal demonstrations
Yuxiang Li, Ian Kash, Katja Hofmann
The 14th European Workshop on Reinforcement Learning (EWRL 2018) | October 2018
Advancements in Dueling Bandits
Yanan Sui, Masrour Zoghi, Katja Hofmann, Yisong Yue
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence | July 2018
Depth and nonlinearity induce implicit exploration for RL
Justas Dauparas, Ryota Tomioka, Katja Hofmann
ICML workshop on Exploration in RL | July 2018
Meta Reinforcement Learning with Latent Variable Gaussian Processes
Steindór Sæmundsson, Katja Hofmann, Marc Peter Deisenroth
Conference on Uncertainty in Artificial Intelligence (UAI) | May 2018
Variational Inference for Data-Efficient Model Learning in POMDPs
Sebastian Tschiatschek, Kai Arulkumaran, Jan Stuehmer, Katja Hofmann
MSR-TR-2018-15 | May 2018
Published by Microsoft
Cross Domain Regularization for Neural Ranking Models Using Adversarial Learning
Daniel Cohen, Bhaskar Mitra, Katja Hofmann, W. Bruce Croft
Proceedings of the 41st international ACM SIGIR conference on Research & development in information retrieval | May 2018
Best Short Research Paper
A New AI Evaluation Cosmos: Ready to Play the Game?
José Hérnandez-Orallo, Marco Baroni, Jordi Bieger, Nader Chmait, David L. Dowe, Katja Hofmann, Fernando Martínez-Plumed, Claes Strannegård, Kristinn R. Thórisson
AI Magazine | September 2017, Vol 38
A Deep Learning Approach for Joint Video Frame and Reward Prediction in Atari Games
Felix Leibfried, Nate Kushman, Katja Hofmann
ICML workshop on Principled Approaches to Deep Learning | August 2017
Asynchronous Data Aggregation for Training End to End Visual Control Networks
Mathew Monfort, Matthew Johnson, Aude Oliva, Katja Hofmann
AAMAS '17 Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems | May 2017
Spontaneous Interactions with a Virtually Embodied Intelligent Assistant in Minecraft
Fraser Allison, Ewa Luger, Katja Hofmann
CHI EA '17 Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems | May 2017
The Atari Grand Challenge Dataset
Vitaly Kurin, Sebastian Nowozin, Katja Hofmann, Lucas Beyer, Bastian Leibe
MSR-TR-2017-61 | May 2017
Published by Microsoft
Memory Lens – How Much Memory Does an Agent Use?
Christoph Dann, Katja Hofmann, Sebastian Nowozin
The 13th European Workshop on Reinforcement Learning (EWRL) 2016 | December 2016
Also presented at the Interpretable ML for Complex Systems Workshop at NeurIPS 2016
Decoding multitask DQN in the world of Minecraft
Lydia T. Liu, Urun Dogan, Katja Hofmann
The 13th European Workshop on Reinforcement Learning (EWRL) 2016 | December 2016
Also presented at the 11th Women in Machine Learning Workshop and the Deep Reinforcement Learning Workshop at NeurIPS 2016.
Experimental and Causal View on Information Integration in Autonomous Agents
Philipp Geiger, Katja Hofmann, Bernhard Schölkopf
6th International Workshop on Combinations of Intelligent Methods and Applications | August 2016
6th International Workshop on Combinations of Intelligent Methods and Applications
The Malmo Platform for Artificial Intelligence Experimentation
Matthew Johnson, Katja Hofmann, Tm Hutton, David Bignell, Katja Hofmann
25th International Joint Conference on Artificial Intelligence (IJCAI-16) | July 2016
Collective Noise Contrastive Estimation for Policy Transfer Learning
Weinan Zhang, Ulrich Paquet, Katja Hofmann
Thirtieth AAAI Conference on Artificial Intelligence (AAAI 2016) | February 2016
Contextual Dueling Bandits
Miro Dudík, Katja Hofmann, Robert E. Schapire, Aleksandrs Slivkins, Masrour Zoghi
Proceedings of The 28th Conference on Learning Theory (COLT) | July 2015
Proceedings of The 28th Conference on Learning Theory (COLT)
Online Learning to Rank: Absolute vs. Relative
Yiwei Chen, Katja Hofmann
Proceedings of the 24th international conference on World Wide Web (WWW) | May 2015
An Eye-tracking Study of User Interactions with Query Auto Completion
Katja Hofmann, Bhaskar Mitra, Filip Radlinski, Milad Shokouhi
Proceedings of the 23rd ACM International Conference on Information and Knowledge Management (CIKM) | November 2014
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How Humans Perceive Human-like Behavior in Video Game Navigation
Evelyn Zuniga, Stephanie Milani, Guy Leroy, Jaroslaw Rzepecki, Raluca Stevenson, Ida Momennejad, Dave Bignell, Mingfei Sun, Alison Shaw, Gavin Costello, Mikhail Jacob, Sam Devlin, Katja Hofmann
CHI 2022 | April 2022
Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors
Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Ed Cutrell, Matthew Tobias Harris, Katja Hofmann
International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS) | October 2021
ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition
Daniela Massiceti, Luisa Zintgraf, John Bronskill, Lida Theodorou, Matthew Tobias Harris, Ed Cutrell, Cecily Morrison, Katja Hofmann, Simone Stumpf
ICCV 2021 | October 2021
Automatic Curriculum Learning for Deep RL: A Short Survey
Rémy Portelas, Cédric Colas, Lilian Weng, Katja Hofmann, Pierre-Yves Oudeyer
International Joint Conference on Artificial Intelligence | March 2020
How Players Speak to an Intelligent Game Character Using Natural Language Messages
Fraser Allison, Ewa Luger, Katja Hofmann
Transactions of the Digital Games Research Association | December 2018, Vol 4(2): pp. 1-49
Spontaneous Interactions with a Virtually Embodied Intelligent Assistant in Minecraft
Fraser Allison, Ewa Luger, Katja Hofmann
CHI EA '17 Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems | May 2017
An Eye-tracking Study of User Interactions with Query Auto Completion
Katja Hofmann, Bhaskar Mitra, Filip Radlinski, Milad Shokouhi
Proceedings of the 23rd ACM International Conference on Information and Knowledge Management (CIKM) | November 2014
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ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition
Daniela Massiceti, Luisa Zintgraf, John Bronskill, Lida Theodorou, Matthew Tobias Harris, Ed Cutrell, Cecily Morrison, Katja Hofmann, Simone Stumpf
ICCV 2021 | October 2021
Asynchronous Data Aggregation for Training End to End Visual Control Networks
Mathew Monfort, Matthew Johnson, Aude Oliva, Katja Hofmann
AAMAS '17 Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems | May 2017
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Cross Domain Regularization for Neural Ranking Models Using Adversarial Learning
Daniel Cohen, Bhaskar Mitra, Katja Hofmann, W. Bruce Croft
Proceedings of the 41st international ACM SIGIR conference on Research & development in information retrieval | May 2018
Best Short Research Paper
Online Evaluation for Information Retrieval
Katja Hofmann, Lihong Li, Filip Radlinski
Foundations and Trends® in Information Retrieval | June 2016, Vol 10: pp. 1-117
Towards Conversational Recommender Systems
Konstantina Christakopoulou, Filip Radlinski, Katja Hofmann
22nd ACM SigKDD Conference on Knowledge Discovery and Data Mining | June 2016
Predicting Search Satisfaction Metrics with Interleaved Comparisons
Anne Schuth, Katja Hofmann, Filip Radlinski
Proceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR) | August 2015
Proceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR)
Online Learning to Rank: Absolute vs. Relative
Yiwei Chen, Katja Hofmann
Proceedings of the 24th international conference on World Wide Web (WWW) | May 2015
An Eye-tracking Study of User Interactions with Query Auto Completion
Katja Hofmann, Bhaskar Mitra, Filip Radlinski, Milad Shokouhi
Proceedings of the 23rd ACM International Conference on Information and Knowledge Management (CIKM) | November 2014
On User Interactions with Query Auto-Completion
Bhaskar Mitra, Milad Shokouhi, Filip Radlinski, Katja Hofmann
Proceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR) | July 2014
Effects of Position Bias on Click-Based Recommender Evaluation
Katja Hofmann, Anne Schuth, Alejandro Bellogin, Maarten de Rijke
36th European Conference on Information Retrieval (ECIR'14) | January 2014
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Lerot: An Online Learning to Rank Framework
Anne Schuth, Katja Hofmann, Shimon Whiteson, Maarten de Rijke
Living Lab'13: Workshop on Living Labs for Information Retrieval Evaluation | January 2013
Living Lab'13: Workshop on Living Labs for Information Retrieval Evaluation
Publications by Type
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Learning Safety Constraints from Demonstrations with Unknown Rewards
David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
International Conference on Artificial Intelligence and Statistics | April 2024
Comparing the Efficacy of Fine-Tuning and Meta-Learning for Few-Shot Policy Imitation
Massimiliano Patacchiola, Mingfei Sun, Katja Hofmann, Richard E Turner
Conference on Lifelong Learning Agents | November 2023
Trust Region Bounds for Decentralized PPO Under Non-stationarity
Mingfei Sun, Sam Devlin, Jacob Beck, Katja Hofmann, Shimon Whiteson
International Conference on Autonomous Agents and Multiagent Systems (AAMAS) | May 2023
Best Paper Award
Imitating Human Behaviour with Diffusion Models
Tim Pearce, Tabish Rashid, Anssi Kanervisto, Dave Bignell, Mingfei Sun, Raluca Stevenson, Sergio Valcarcel Macua, Shanzheng Tan, Ida Momennejad, Katja Hofmann, Sam Devlin
ICLR 2023 | May 2023
Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games
Stephanie Milani, Arthur Juliani, Ida Momennejad, Raluca Stevenson, Jaroslaw Rzepecki, Alison Shaw, Gavin Costello, Fei Fang, Sam Devlin, Katja Hofmann
CHI | April 2023
Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification
Massimiliano Patacchiola, John F Bronskill, Aliaksandra Shysheya, Katja Hofmann, Sebastian Nowozin, Richard E Turner
NeurIPS 2022 | November 2022
Uni[MASK]: Unified Inference in Sequential Decision Problems
Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, Dave Bignell, Stephanie Milani, Katja Hofmann, Matthew Hausknecht, Anca Dragan, Sam Devlin
2022 Neural Information Processing Systems | November 2022
Interactively Learning Preference Constraints in Linear Bandits
David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
ICML 2022 | June 2022
How Humans Perceive Human-like Behavior in Video Game Navigation
Evelyn Zuniga, Stephanie Milani, Guy Leroy, Jaroslaw Rzepecki, Raluca Stevenson, Ida Momennejad, Dave Bignell, Mingfei Sun, Alison Shaw, Gavin Costello, Mikhail Jacob, Sam Devlin, Katja Hofmann
CHI 2022 | April 2022
Deterministic and Discriminative Imitation (D2-Imitation): Revisiting Adversarial Imitation for Sample Efficiency
Mingfei Sun, Sam Devlin, Katja Hofmann, Shimon Whiteson
AAAI 2022 | February 2022
Grounding Spatio-Temporal Language with Transformers
Tristan Karch, Laetitia Teodorescu, Katja Hofmann, Clément Moulin-Frier, Pierre-Yves Oudeyer
NeurIPS 2021 | December 2021
Memory Efficient Meta-Learning with Large Images
John Bronskill, Daniela Massiceti, Massimiliano Patacchiola, Katja Hofmann, Richard Turner
NeurIPS 2021 | December 2021
Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors
Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Ed Cutrell, Matthew Tobias Harris, Katja Hofmann
International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS) | October 2021
ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition
Daniela Massiceti, Luisa Zintgraf, John Bronskill, Lida Theodorou, Matthew Tobias Harris, Ed Cutrell, Cecily Morrison, Katja Hofmann, Simone Stumpf
ICCV 2021 | October 2021
Strategically Efficient Exploration in Competitive Multiagent Reinforcement Learning
Robert Loftin, Aadirupa Saha, Sam Devlin, Katja Hofmann
Conference on Uncertainty in Artificial Intelligence (UAI) 2021 | July 2021
Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation
Sam Devlin, Raluca Stevenson, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann
2021 International Conference on Machine Learning | July 2021
Source code available at: https://github.com/microsoft/NTT
TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL
Clément Romac, Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer
2021 International Conference on Machine Learning | July 2021
Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning
Luisa Zintgraf, Leo Feng, Cong Lu, Maximilian Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson
2021 International Conference on Machine Learning | July 2021
Deep Interactive Bayesian Reinforcement Learning via Meta-Learning
Luisa Zintgraf, Sam Devlin, Kamil Ciosek, Shimon Whiteson, Katja Hofmann
20th International Conference on Autonomous Agents and Multiagent Systems | May 2021
Evaluating the Robustness of Collaborative Agents
Paul Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca Dragan, Rohin Shah
20th International Conference on Autonomous Agents and Multiagent Systems | May 2021
“It’s Unwieldy and It Takes a Lot of Time.” Challenges and Opportunities for Creating Agents in Commercial Games
Mikhail Jacob, Sam Devlin, Katja Hofmann
16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment | October 2020
AIIDE 2020 BEST PAPER AWARD
Best paper award winner.
Variational Integrator Networks for Physically Meaningful Embeddings
Steindór Sæmundsson, Alexander Terenin, Katja Hofmann, Marc Peter Deisenroth
Twenty-Third International Conference on Artificial Intelligence and Statistics (AISTATS) | June 2020
Combining No-regret and Q-learning
Ian A. Kash, Michael Sullins, Katja Hofmann
2020 Adaptive Agents and Multi-Agents Systems | May 2020
A Novel Individually Rational Objective In Multi-Agent Multi-Armed Bandit: Algorithms and Regret Bounds
Aristide Tossou, Christos Dimitrakakis, Jaroslaw Rzepecki, Katja Hofmann
International Conference on Autonomous Agents and Multiagent Systems (AAMAS) | May 2020
VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning
Luisa Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson
Eighth International Conference on Learning Representations (ICLR) | April 2020
Conservative Uncertainty Estimation By Fitting Prior Networks
Kamil Ciosek, Vincent Fortuin, Ryota Tomioka, Katja Hofmann, Richard Turner
Eighth International Conference on Learning Representations (ICLR) | April 2020
AMRL: Aggregated Memory For Reinforcement Learning
Jacob Beck, Kamil Ciosek, Sam Devlin, Sebastian Tschiatschek, Cheng Zhang, Katja Hofmann
Eighth International Conference on Learning Representations (ICLR) | April 2020
Automatic Curriculum Learning for Deep RL: A Short Survey
Rémy Portelas, Cédric Colas, Lilian Weng, Katja Hofmann, Pierre-Yves Oudeyer
International Joint Conference on Artificial Intelligence | March 2020
Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck
Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann
Thirty-third Conference on Neural Information Processing Systems (NeurIPS) | December 2019
Better Exploration with Optimistic Actor-Critic
Kamil Ciosek, Quan Vuong, Robert Loftin, Katja Hofmann
33rd Conference on Neural Information Processing Systems (NeurIPS) | December 2019
Reinforcement Learning: Past, Present, and Future Perspectives
Thirty-third Conference on Neural Information Processing Systems (NeurIPS) | December 2019
Tutorial
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning
David Janz, Jiri Hron, Przemysław Mazur, Katja Hofmann, Jose Miguel Hernandez Lobato, Sebastian Tschiatschek
Thirty-third Conference on Neural Information Processing Systems (NeurIPS) | December 2019
The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors
William H Guss, Cayden Codel, Katja Hofmann, Brandon Houghton, Noboru Sean Kuno, Stephanie Milani, Sharada Mohanty, Diego Perez Liebana, Ruslan Salakhutdinov, Nicholay Topin, Manuela Veloso, Philip Wang
Thirty-third Conference on Neural Information Processing Systems (NeurIPS) Competition track | December 2019
Minecraft as AI Playground and Laboratory
Proceedings of the Annual Symposium on Computer-Human Interaction in Play (ChiPlay) | November 2019
Opening keynote (extended abstract)
Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments
Rémy Portelas, Pierre-Yves Oudeyer, Cédric Colas, Katja Hofmann
Third Conference on Robot Learning (CoRL) | October 2019
MazeExplorer: A Customisable 3D Benchmark for Assessing Generalisation in Reinforcement Learning
Luke Harries, Sebastian Lee, Jaroslaw Rzepecki, Katja Hofmann, Sam Devlin
IEEE Conference on Games | August 2019
Win or Learn Fast Proximal Policy Optimisation
Dino Ratcliffe, Katja Hofmann, Sam Devlin
IEEE Conference on Games | August 2019
Fast Context Adaptation via Meta-Learning
Luisa Zintgraf, Kyriacos Shiarlis, Vitaly Kurin, Katja Hofmann, Shimon Whiteson
Thirty-sixth International Conference on Machine Learning (ICML) | June 2019
Combining No-regret and Q-learning (2018)
Ian Kash, Katja Hofmann
The 14th European Workshop on Reinforcement Learning (EWRL 2018) | October 2018
Also presented at the AAAI-19 workshop on Reinforcement Learning in Games.
Learning good policies from suboptimal demonstrations
Yuxiang Li, Ian Kash, Katja Hofmann
The 14th European Workshop on Reinforcement Learning (EWRL 2018) | October 2018
Advancements in Dueling Bandits
Yanan Sui, Masrour Zoghi, Katja Hofmann, Yisong Yue
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence | July 2018
Depth and nonlinearity induce implicit exploration for RL
Justas Dauparas, Ryota Tomioka, Katja Hofmann
ICML workshop on Exploration in RL | July 2018
Meta Reinforcement Learning with Latent Variable Gaussian Processes
Steindór Sæmundsson, Katja Hofmann, Marc Peter Deisenroth
Conference on Uncertainty in Artificial Intelligence (UAI) | May 2018
Cross Domain Regularization for Neural Ranking Models Using Adversarial Learning
Daniel Cohen, Bhaskar Mitra, Katja Hofmann, W. Bruce Croft
Proceedings of the 41st international ACM SIGIR conference on Research & development in information retrieval | May 2018
Best Short Research Paper
A Deep Learning Approach for Joint Video Frame and Reward Prediction in Atari Games
Felix Leibfried, Nate Kushman, Katja Hofmann
ICML workshop on Principled Approaches to Deep Learning | August 2017
Asynchronous Data Aggregation for Training End to End Visual Control Networks
Mathew Monfort, Matthew Johnson, Aude Oliva, Katja Hofmann
AAMAS '17 Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems | May 2017
Spontaneous Interactions with a Virtually Embodied Intelligent Assistant in Minecraft
Fraser Allison, Ewa Luger, Katja Hofmann
CHI EA '17 Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems | May 2017
Memory Lens – How Much Memory Does an Agent Use?
Christoph Dann, Katja Hofmann, Sebastian Nowozin
The 13th European Workshop on Reinforcement Learning (EWRL) 2016 | December 2016
Also presented at the Interpretable ML for Complex Systems Workshop at NeurIPS 2016
Decoding multitask DQN in the world of Minecraft
Lydia T. Liu, Urun Dogan, Katja Hofmann
The 13th European Workshop on Reinforcement Learning (EWRL) 2016 | December 2016
Also presented at the 11th Women in Machine Learning Workshop and the Deep Reinforcement Learning Workshop at NeurIPS 2016.
Experimental and Causal View on Information Integration in Autonomous Agents
Philipp Geiger, Katja Hofmann, Bernhard Schölkopf
6th International Workshop on Combinations of Intelligent Methods and Applications | August 2016
6th International Workshop on Combinations of Intelligent Methods and Applications
The Malmo Platform for Artificial Intelligence Experimentation
Matthew Johnson, Katja Hofmann, Tm Hutton, David Bignell, Katja Hofmann
25th International Joint Conference on Artificial Intelligence (IJCAI-16) | July 2016
Towards Conversational Recommender Systems
Konstantina Christakopoulou, Filip Radlinski, Katja Hofmann
22nd ACM SigKDD Conference on Knowledge Discovery and Data Mining | June 2016
Collective Noise Contrastive Estimation for Policy Transfer Learning
Weinan Zhang, Ulrich Paquet, Katja Hofmann
Thirtieth AAAI Conference on Artificial Intelligence (AAAI 2016) | February 2016
Predicting Search Satisfaction Metrics with Interleaved Comparisons
Anne Schuth, Katja Hofmann, Filip Radlinski
Proceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR) | August 2015
Proceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR)
Contextual Dueling Bandits
Miro Dudík, Katja Hofmann, Robert E. Schapire, Aleksandrs Slivkins, Masrour Zoghi
Proceedings of The 28th Conference on Learning Theory (COLT) | July 2015
Proceedings of The 28th Conference on Learning Theory (COLT)
Online Learning to Rank: Absolute vs. Relative
Yiwei Chen, Katja Hofmann
Proceedings of the 24th international conference on World Wide Web (WWW) | May 2015
An Eye-tracking Study of User Interactions with Query Auto Completion
Katja Hofmann, Bhaskar Mitra, Filip Radlinski, Milad Shokouhi
Proceedings of the 23rd ACM International Conference on Information and Knowledge Management (CIKM) | November 2014
On User Interactions with Query Auto-Completion
Bhaskar Mitra, Milad Shokouhi, Filip Radlinski, Katja Hofmann
Proceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR) | July 2014
Effects of Position Bias on Click-Based Recommender Evaluation
Katja Hofmann, Anne Schuth, Alejandro Bellogin, Maarten de Rijke
36th European Conference on Information Retrieval (ECIR'14) | January 2014
Lerot: An Online Learning to Rank Framework
Anne Schuth, Katja Hofmann, Shimon Whiteson, Maarten de Rijke
Living Lab'13: Workshop on Living Labs for Information Retrieval Evaluation | January 2013
Living Lab'13: Workshop on Living Labs for Information Retrieval Evaluation
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Scaling Laws for Pre-training Agents and World Models
Tim Pearce, Tabish Rashid, Dave Bignell, Raluca Stevenson, Sam Devlin, Katja Hofmann
November 2024
Transformer Neural Autoregressive Flows
Massimiliano Patacchiola, Aliaksandra Shysheya, Katja Hofmann, Richard E Turner
January 2024
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Toward Human-AI Alignment in Large-Scale Multi-Player Games
Sugandha Sharma, Guy Davidson, Khimya Khetarpal, Anssi Kanervisto, Udit Arora, Katja Hofmann, Ida Momennejad
arXiv:2402.03575 | February 2024
Published by Microsoft
The Multi-Agent Reinforcement Learning in MalmÖ (MARLÖ) Competition
Diego Perez-Liebana, Katja Hofmann, Sharada Prasanna Mohanty, Noboru Sean Kuno, Andre Kramer, Sam Devlin, Raluca D. Gaina, Daniel Ionita
1901.08129 | January 2019
Published by Arxiv
Variational Inference for Data-Efficient Model Learning in POMDPs
Sebastian Tschiatschek, Kai Arulkumaran, Jan Stuehmer, Katja Hofmann
MSR-TR-2018-15 | May 2018
Published by Microsoft
The Atari Grand Challenge Dataset
Vitaly Kurin, Sebastian Nowozin, Katja Hofmann, Lucas Beyer, Bastian Leibe
MSR-TR-2017-61 | May 2017
Published by Microsoft
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SpatialSim: Recognizing Spatial Configurations of Objects with Graph Neural Networks
Laetitia Teodorescu, Katja Hofmann, Pierre-Yves Oudeyer1
Frontiers in Artificial Intelligence | January 2022, Vol 4
How Players Speak to an Intelligent Game Character Using Natural Language Messages
Fraser Allison, Ewa Luger, Katja Hofmann
Transactions of the Digital Games Research Association | December 2018, Vol 4(2): pp. 1-49
A New AI Evaluation Cosmos: Ready to Play the Game?
José Hérnandez-Orallo, Marco Baroni, Jordi Bieger, Nader Chmait, David L. Dowe, Katja Hofmann, Fernando Martínez-Plumed, Claes Strannegård, Kristinn R. Thórisson
AI Magazine | September 2017, Vol 38
Online Evaluation for Information Retrieval
Katja Hofmann, Lihong Li, Filip Radlinski
Foundations and Trends® in Information Retrieval | June 2016, Vol 10: pp. 1-117