… In this paper, a reinforcement learning approach to autonomous goal regulation is
proposed, based on the self-evolution framework addressed by Shin et al. (2009a) and its …

… EAs and RL from different perspectives to solve problems more efficiently. For brevity, we
refer to the related works in this area as Evolutionary Reinforcement Learning (ERL). However, …

… This article focuses on the division of labor between evolution … of tools, called reinforcement
learning methods. These … In addition, reinforcement learning methods are well-suited …

… evolutionary computation to train artificial neural networks, or neuroevolution (NE), for
reinforcement learning (… The approach is demonstrated successfully on two reinforcement learning …

… reinforcement learning, namely a preference-based variant of a direct policy search method
based on evolutionary … Embedding the racing algorithm in a rank-based evolutionary search …

… These include established subfields such as evolutionary reinforcement learning , but
also newer topics such as relational knowledge representation approaches and Bayesian …

… As a particularly suitable candidate, reinforcement learning (… The marriage between RL
and evolutionary game may be a … in the evolutionary games with the reinforcement learning (…

… In this article, we explore an evolutionary … in reinforcement learning. Shaping rewards is a
frequently used approach to increase the learning performance of reinforcement learning, with …

… reinforcement learning models to capture neural and cognitive function. But reinforcement
learning, as a … Reinforcement learning is often viewed in mechanistic terms – as describing the …

… Learning – Evolutionary Reinforcement Learning (UL-ERL) approach to the challenging
reinforcement learning … using vision from the driver’s perspective as input. The high-dimensional …