research
∙
01/18/2023
Sample-Efficient Multi-Objective Learning via Generalized Policy Improvement Prioritization
Multi-objective reinforcement learning (MORL) algorithms tackle sequenti...
share
research
∙
06/22/2022
Optimistic Linear Support and Successor Features as a Basis for Optimal Policy Transfer
In many real-world applications, reinforcement learning (RL) agents migh...
research
∙
03/18/2022
Improving Urban Mobility: using artificial intelligence and new technologies to connect supply and demand
As the demand for mobility in our society seems to increase, the various...
research
∙
05/20/2021
Minimum-Delay Adaptation in Non-Stationary Reinforcement Learning via Online High-Confidence Change-Point Detection
Non-stationary environments are challenging for reinforcement learning a...
research
∙
06/15/2020
Quantitatively Assessing the Benefits of Model-driven Development in Agent-based Modeling and Simulation
The agent-based modeling and simulation (ABMS) paradigm has been used to...
research
∙
04/09/2020
Quantifying the Impact of Non-Stationarity in Reinforcement Learning-Based Traffic Signal Control
In reinforcement learning (RL), dealing with non-stationarity is a chall...
research
∙
02/22/2016
