Abstract
The reinforcement learning research area contains a wide range of methods for solving the problems of intelligent agent control. Despite the progress that has been made, the task of creating a highly autonomous agent is still a significant challenge. One potential solution to this problem is intrinsic motivation, a concept derived from developmental psychology. This review considers the existing methods for determining intrinsic motivation based on the world model obtained by the agent. We propose a systematic approach to current research in this field, which consists of three categories of methods, distinguished by the way they utilize a world model in the agent's components: complementary intrinsic reward, exploration policy, and intrinsically motivated goals. The proposed unified framework describes the architecture of agents using a world model and intrinsic motivation to improve learning. The potential for developing new techniques in this area of research is also examined.
Abstract (translated)
强化学习研究领域包含了解决智能代理控制问题的各种方法。尽管已经取得了进展,但创造高度自主的代理仍然是一个重大的挑战。解决这个问题的一个潜在方法是内生动机,这是一个从发展心理学中衍生的概念。本综述考虑了基于代理获得的世界模型来确定内生动机的现有方法。我们提出了一种系统的研究方法,该方法包括三个类别的方法,区别在于它们在代理组件中使用的世界模型:互补的内生奖励、探索策略和内生动机目标。 proposed unified framework描述了使用世界模型和内生动机来提高学习代理的架构。此外,该研究领域开发新技术的潜力也被研究了。
URL
https://arxiv.org/abs/2301.10067
