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Sensors (Basel, Switzerland)
May 19, 2022
Autonomous navigation in dynamic environments where people move unpredictably is an essential task for service robots in real-world populated scenarios. Recent works in reinforcement learning (RL) have been applied to autonomous vehicle driving and t...
IEEE transactions on cybernetics
May 19, 2022
Encouraging the agent to explore has always been an important and challenging topic in the field of reinforcement learning (RL). Distributional representation for network parameters or value functions is usually an effective way to improve the explor...
Scientific reports
May 18, 2022
Career planning consists of a series of decisions that will significantly impact one's life. However, current recommendation systems have serious limitations, including the lack of effective artificial intelligence algorithms for long-term career pla...
IEEE transactions on neural networks and learning systems
May 2, 2022
Bin-packing problem (BPP) is a typical combinatorial optimization problem whose decision-making process is NP-hard. This article examines BPPs in varying environments, where random number and shape of items are to be packed in different instances. Th...
IEEE transactions on neural networks and learning systems
May 2, 2022
In this article, we consider a subclass of partially observable Markov decision process (POMDP) problems which we termed confounding POMDPs. In these types of POMDPs, temporal difference (TD)-based reinforcement learning (RL) algorithms struggle, as ...
Neural networks : the official journal of the International Neural Network Society
Apr 21, 2022
This paper addresses a new interpretation of the traditional optimization method in reinforcement learning (RL) as optimization problems using reverse Kullback-Leibler (KL) divergence, and derives a new optimization method using forward KL divergence...
Neural networks : the official journal of the International Neural Network Society
Apr 19, 2022
Deep learning (DL) and reinforcement learning (RL) methods seem to be a part of indispensable factors to achieve human-level or super-human AI systems. On the other hand, both DL and RL have strong connections with our brain functions and with neuros...
Neural networks : the official journal of the International Neural Network Society
Apr 16, 2022
Autonomous systems are becoming ubiquitous and gaining momentum within the marine sector. Since the electrification of transport is happening simultaneously, autonomous marine vessels can reduce environmental impact, lower costs, and increase efficie...
Science robotics
Apr 6, 2022
Robots need robust models to effectively perform tasks that humans do on a daily basis. These models often require substantial developmental costs to maintain because they need to be adjusted and adapted over time. Deep reinforcement learning is a po...
Neural networks : the official journal of the International Neural Network Society
Mar 23, 2022
Rapid advancements in deep learning have led to many recent breakthroughs. While deep learning models achieve superior performance, often statistically better than humans, their adoption into safety-critical settings, such as healthcare or self-drivi...