Goran Radanovic

Orcid: 0000-0001-6016-4013

According to our database1, Goran Radanovic authored at least 51 papers between 2013 and 2024.

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Bibliography

2024
Performative Reinforcement Learning in Gradually Shifting Environments.
CoRR, 2024

Corruption Robust Offline Reinforcement Learning with Human Feedback.
CoRR, 2024

Learning Embeddings for Sequential Tasks Using Population of Agents.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Agent-Specific Effects: A Causal Effect Propagation Analysis in Multi-Agent MDPs.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Reward Model Learning vs. Direct Policy Optimization: A Comparative Analysis of Learning from Human Preferences.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Reward Design for Justifiable Sequential Decision-Making.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Corruption-Robust Offline Two-Player Zero-Sum Markov Games.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Defense Against Reward Poisoning Attacks in Reinforcement Learning.
Trans. Mach. Learn. Res., 2023

Agent-Specific Effects.
CoRR, 2023

Sequential Principal-Agent Problems with Communication: Efficient Computation and Learning.
CoRR, 2023

Performative Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023

Towards Computationally Efficient Responsibility Attribution in Decentralized Partially Observable MDPs.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

Implicit Poisoning Attacks in Two-Agent Reinforcement Learning: Adversarial Policies for Training-Time Attacks.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

Online Defense Strategies for Reinforcement Learning Against Adaptive Reward Poisoning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Online Reinforcement Learning with Uncertain Episode Lengths.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Markov Decision Processes with Time-Varying Geometric Discounting.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Envy-free Policy Teaching to Multiple Agents.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sequential Decision Making With Information Asymmetry (Invited Talk).
Proceedings of the 33rd International Conference on Concurrency Theory, 2022

Actual Causality and Responsibility Attribution in Decentralized Partially Observable Markov Decision Processes.
Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

Bayesian Persuasion in Sequential Decision-Making.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Admissible Policy Teaching through Reward Design.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Policy Teaching in Reinforcement Learning via Environment Poisoning Attacks.
J. Mach. Learn. Res., 2021

Diversity in News Recommendation (Dagstuhl Perspectives Workshop 19482).
Dagstuhl Manifestos, 2021

Reinforcement Learning for Education: Opportunities and Challenges.
CoRR, 2021

On Blame Attribution for Accountable Multi-Agent Sequential Decision Making.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Explicable Reward Design for Reinforcement Learning Agents.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Robust Helpful Behaviors in Two-Player Cooperative Atari Environments.
Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2020
Diversity in News Recommendations.
CoRR, 2020

How do fairness definitions fare? Testing public attitudes towards three algorithmic definitions of fairness in loan allocations.
Artif. Intell., 2020

Policy Teaching via Environment Poisoning: Training-time Adversarial Attacks against Reinforcement Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

The Effectiveness of Peer Prediction in Long-Term Forecasting.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Learning to Collaborate in Markov Decision Processes.
Proceedings of the 36th International Conference on Machine Learning, 2019

How Do Fairness Definitions Fare?: Examining Public Attitudes Towards Algorithmic Definitions of Fairness.
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

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

2018
Information Gathering With Peers: Submodular Optimization With Peer-Prediction Constraints.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Partial Truthfulness in Minimal Peer Prediction Mechanisms With Limited Knowledge.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Game Theory for Data Science: Eliciting Truthful Information
Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers, ISBN: 978-3-031-01577-9, 2017

Mechanismen zur Beschaffung korrekter Daten.
Inform. Spektrum, 2017

Calibrated Fairness in Bandits.
CoRR, 2017

Peer Truth Serum: Incentives for Crowdsourcing Measurements and Opinions.
CoRR, 2017

Subjective fairness: Fairness is in the eye of the beholder.
CoRR, 2017

Multi-View Decision Processes: The Helper-AI Problem.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Elicitation and Aggregation of Crowd Information.
PhD thesis, 2016

Incentives for Effort in Crowdsourcing Using the Peer Truth Serum.
ACM Trans. Intell. Syst. Technol., 2016

Learning to Scale Payments in Crowdsourcing with PropeRBoost.
Proceedings of the Fourth AAAI Conference on Human Computation and Crowdsourcing, 2016

Limiting the Influence of Low Quality Information in Community Sensing.
Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, 2016

2015
Incentivizing truthful responses with the logarithmic peer truth serum.
Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers, 2015

Incentive Schemes for Participatory Sensing.
Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, 2015

Incentives for Subjective Evaluations with Private Beliefs.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Incentives for Truthful Information Elicitation of Continuous Signals.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
A Robust Bayesian Truth Serum for Non-Binary Signals.
Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013


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