Timezone: »
Poster
Multi-objective Bandits: Optimizing the Generalized Gini Index
Robert Busa-Fekete · Balazs Szorenyi · Paul Weng · Shie Mannor
We study the multi-armed bandit (MAB) problem where the agent receives a vectorial feedback that encodes many possibly competing objectives to be optimized. The goal of the agent is to find a policy, which can optimize these objectives simultaneously in a fair way. This multi-objective online optimization problem is formalized by using the Generalized Gini Index (GGI) aggregation function. We propose an online gradient descent algorithm which exploits the convexity of the GGI aggregation function, and controls the exploration in a careful way achieving a distribution-free regret $\tilde{\bigO} (T^{-1/2} )$ with high probability. We test our algorithm on synthetic data as well as on an electric battery control problem where the goal is to trade off the use of the different cells of a battery in order to balance their respective degradation rates.
Summary/Notes »Author Information
Robert Busa-Fekete (Yahoo! Research)
Balazs Szorenyi (Technion)
Paul Weng (SYSU-CMU JIE)
Shie Mannor (Technion)
Related Events (a corresponding poster, oral, or spotlight)
-
2017 Talk: Multi-objective Bandits: Optimizing the Generalized Gini Index »
Mon Aug 7th 12:30 -- 12:48 AM Room C4.1
More from the Same Authors
-
2020 Poster: Optimistic Policy Optimization with Bandit Feedback »
Lior Shani · Yonathan Efroni · Aviv Rosenberg · Shie Mannor -
2020 Poster: Topic Modeling via Full Dependence Mixtures »
Dan Fisher · Mark Kozdoba · Shie Mannor -
2019 Poster: Exploration Conscious Reinforcement Learning Revisited »
Lior Shani · Yonathan Efroni · Shie Mannor -
2019 Poster: Action Robust Reinforcement Learning and Applications in Continuous Control »
Chen Tessler · Chen Tessler · Yonathan Efroni · Shie Mannor -
2019 Poster: The Natural Language of Actions »
Guy Tennenholtz · Shie Mannor -
2019 Oral: Exploration Conscious Reinforcement Learning Revisited »
Lior Shani · Yonathan Efroni · Shie Mannor -
2019 Oral: The Natural Language of Actions »
Guy Tennenholtz · Shie Mannor -
2019 Poster: Nonlinear Distributional Gradient Temporal-Difference Learning »
chao qu · Shie Mannor · Huan Xu -
2019 Oral: Action Robust Reinforcement Learning and Applications in Continuous Control »
Chen Tessler · Chen Tessler · Yonathan Efroni · Yonathan Efroni · Shie Mannor · Shie Mannor -
2019 Oral: Nonlinear Distributional Gradient Temporal-Difference Learning »
chao qu · Shie Mannor · Huan Xu -
2018 Poster: Ranking Distributions based on Noisy Sorting »
Adil El Mesaoudi-Paul · Eyke Hüllermeier · Robert Busa-Fekete -
2018 Poster: Beyond the One-Step Greedy Approach in Reinforcement Learning »
Yonathan Efroni · Gal Dalal · Bruno Scherrer · Shie Mannor -
2018 Oral: Beyond the One-Step Greedy Approach in Reinforcement Learning »
Yonathan Efroni · Gal Dalal · Bruno Scherrer · Shie Mannor -
2018 Oral: Ranking Distributions based on Noisy Sorting »
Adil El Mesaoudi-Paul · Eyke Hüllermeier · Robert Busa-Fekete -
2017 Workshop: Lifelong Learning: A Reinforcement Learning Approach »
Sarath Chandar · Balaraman Ravindran · Daniel J. Mankowitz · Shie Mannor · Tom Zahavy -
2017 Poster: Consistent On-Line Off-Policy Evaluation »
Assaf Hallak · Shie Mannor -
2017 Talk: Consistent On-Line Off-Policy Evaluation »
Assaf Hallak · Shie Mannor -
2017 Poster: End-to-End Differentiable Adversarial Imitation Learning »
Nir Baram · Oron Anschel · Itai Caspi · Shie Mannor -
2017 Talk: End-to-End Differentiable Adversarial Imitation Learning »
Nir Baram · Oron Anschel · Itai Caspi · Shie Mannor
