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03/16/2023
Learning Rewards to Optimize Global Performance Metrics in Deep Reinforcement Learning
When applying reinforcement learning (RL) to a new problem, reward engin...
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10/07/2021
Generalization in Deep RL for TSP Problems via Equivariance and Local Search
Deep reinforcement learning (RL) has proved to be a competitive heuristi...
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10/06/2021
Improving Generalization of Deep Reinforcement Learning-based TSP Solvers
Recent work applying deep reinforcement learning (DRL) to solve travelin...
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03/15/2021
Learning Symbolic Rules for Interpretable Deep Reinforcement Learning
Recent progress in deep reinforcement learning (DRL) can be largely attr...
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02/26/2021
Safe Distributional Reinforcement Learning
Safety in reinforcement learning (RL) is a key property in both training...
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02/19/2021
Analytics and Machine Learning in Vehicle Routing Research
The Vehicle Routing Problem (VRP) is one of the most intensively studied...
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08/18/2020
Learning Fair Policies in Multiobjective (Deep) Reinforcement Learning with Average and Discounted Rewards
As the operations of autonomous systems generally affect simultaneously ...
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05/29/2020
Reinforcement Learning
Reinforcement learning (RL) is a general framework for adaptive control,...
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10/19/2019
Towards More Sample Efficiency in Reinforcement Learning with Data Augmentation
Deep reinforcement learning (DRL) is a promising approach for adaptive r...
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10/19/2019
Towards More Sample Efficiency inReinforcement Learning with Data Augmentation
Deep reinforcement learning (DRL) is a promising approach for adaptive r...
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09/24/2019
Invariant Transform Experience Replay
Deep reinforcement learning (DRL) is a promising approach for adaptive r...
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07/24/2019
Fairness in Reinforcement Learning
Decision support systems (e.g., for ecological conservation) and autonom...
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06/10/2019
Exploiting the sign of the advantage function to learn deterministic policies in continuous domains
In the context of learning deterministic policies in continuous domains,...
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03/25/2019
Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems
Social recommendation leverages social information to solve data sparsit...
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01/23/2018
An Efficient Primal-Dual Algorithm for Fair Combinatorial Optimization Problems
We consider a general class of combinatorial optimization problems inclu...
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08/23/2017
Optimal Threshold Policies for Robust Data Center Control
With the simultaneous rise of energy costs and demand for cloud computin...
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01/03/2017
From Preference-Based to Multiobjective Sequential Decision-Making
In this paper, we present a link between preference-based and multiobjec...
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01/03/2017
Finding Risk-Averse Shortest Path with Time-dependent Stochastic Costs
In this paper, we tackle the problem of risk-averse route planning in a ...
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12/01/2016
Optimizing Quantiles in Preference-based Markov Decision Processes
In the Markov decision process model, policies are usually evaluated by ...
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11/03/2016
Quantile Reinforcement Learning
In reinforcement learning, the standard criterion to evaluate policies i...
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09/26/2013
Approximation of Lorenz-Optimal Solutions in Multiobjective Markov Decision Processes
This paper is devoted to fair optimization in Multiobjective Markov Deci...
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07/04/2012