Deep reinforcement learning and its applications in medical imaging and radiation therapy: a survey
Reinforcement learning takes sequential decision-making approaches by learning the policy
through trial and error based on interaction with the environment. Combining deep learning …
through trial and error based on interaction with the environment. Combining deep learning …
Learning cut selection for mixed-integer linear programming via hierarchical sequence model
Cutting planes (cuts) are important for solving mixed-integer linear programs (MILPs), which
formulate a wide range of important real-world applications. Cut selection--which aims to …
formulate a wide range of important real-world applications. Cut selection--which aims to …
Quality-similar diversity via population based reinforcement learning
Diversity is a growing research topic in Reinforcement Learning (RL). Previous research on
diversity has mainly focused on promoting diversity to encourage exploration and thereby …
diversity has mainly focused on promoting diversity to encourage exploration and thereby …
Interpretable pipelines with evolutionary optimized modules for reinforcement learning tasks with visual inputs
LL Custode, G Iacca - Proceedings of the Genetic and Evolutionary …, 2022 - dl.acm.org
The importance of explainability in AI has become a pressing concern, for which several
explainable AI (XAI) approaches have been recently proposed. However, most of the …
explainable AI (XAI) approaches have been recently proposed. However, most of the …
A review for deep reinforcement learning in atari: Benchmarks, challenges, and solutions
J Fan - arXiv preprint arXiv:2112.04145, 2021 - arxiv.org
The Arcade Learning Environment (ALE) is proposed as an evaluation platform for
empirically assessing the generality of agents across dozens of Atari 2600 games. ALE …
empirically assessing the generality of agents across dozens of Atari 2600 games. ALE …
PRANCE: Joint Token-Optimization and Structural Channel-Pruning for Adaptive ViT Inference
We introduce PRANCE, a Vision Transformer compression framework that jointly optimizes
the activated channels and reduces tokens, based on the characteristics of inputs …
the activated channels and reduces tokens, based on the characteristics of inputs …
Interpretable pipelines with evolutionarily optimized modules for RL tasks with visual inputs
LL Custode, G Iacca - arXiv preprint arXiv:2202.04943, 2022 - arxiv.org
The importance of explainability in AI has become a pressing concern, for which several
explainable AI (XAI) approaches have been recently proposed. However, most of the …
explainable AI (XAI) approaches have been recently proposed. However, most of the …
Evolutionary Optimization of Decision Trees for Interpretable Reinforcement Learning
LL Custode - 2023 - iris.unitn.it
Abstract While Artificial Intelligence (AI) is making giant steps, it is also raising concerns
about its trustworthiness, due to the fact that widely-used black-box models cannot be …
about its trustworthiness, due to the fact that widely-used black-box models cannot be …
Synchronous Prediction then Instantaneous Optimization for Dynamic Large-Scale Bike-Sharing Repositioning Problem
Z Kang, X Chang, H Sun, X Guo - Available at SSRN 4836034 - papers.ssrn.com
As a convenient and low-carbon transport service to address the “last mile” problem, bike-
sharing systems (BSSs) have been rapidly developed worldwide. However, the salient …
sharing systems (BSSs) have been rapidly developed worldwide. However, the salient …
[PDF][PDF] Combination and Benchmark of RL Models
D Wang, C Houff, E Sudre - codyhouff.github.io
Atari games have been a long-standing benchmark in the reinforcement learning (RL)
community for the past decade. This benchmark was proposed to test general competency …
community for the past decade. This benchmark was proposed to test general competency …