… In our opinion, the evolutionary perspective we adopt resolves what have been some of the
… results of computational experiments involving evolutionary search for RL reward functions [1…

… In contrast, a general computational reward framework from the evolutionary perspective …
environment, the multi-agent evolutionary reinforcement learning (MERL) method maintains …

… an evolutionary perspective, combining RL with EA is closely related to the idea of incorporating
learning with evolution [… idea to tackle catastrophic forgetting in transfer learning [17] and …

… In this paper, we introduce Collaborative Evolutionary Reinforcement Learning (CERL)…
evolutionary perspective, this is closely related to the idea of incorporating learning with evolution …

… of Reinforcement Learning (RL) techniques blends with one or more techniques from
Evolutionary … techniques as the evolutionary computation versus reinforcement learning (ECRL) …

… realms, evolution and reinforcement learning are parallel … world, evolution is antecedent
to all forms of learning but can… , evolutionary computation and reinforcement learning were …

… From the learning perspective, reinforcement learning (RL) shows many parallels with
how humans and animals can deal with new unknown sequential decision-making tasks. …

… of evolutionary reinforcement learning (ERL). ERL [10] is a fusion of EC and reinforcement
learning (RL), in which evolutionary techniques (such as genetic algorithms or evolutionary …

… In this paper, we introduce Evolutionary Reinforcement Learning (… evolutionary perspective,
combining RL with EA is closely related to the idea of incorporating learning with evolution [1…

… We propose Recruitment-imitation Mechanism (RIM) and an evolutionary reinforcement
learning framework that applies this mechanism. At the core of RIM, a dual-policy RL structure is …