Environments for Automatic Curriculum Learning: A Short Survey

IF 0.5 4区 数学 Q3 MATHEMATICS
M. I. Nesterova, A. A. Skrynnik, A. I. Panov
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引用次数: 0

Abstract

Reinforcement learning encompasses various approaches that involve training an agent on multiple tasks. These approaches include training a general agent capable of executing a wide range of tasks and training a specialized agent focused on mastering a specific skill. Curriculum learning strategically orders tasks to optimize the learning process, enhancing training efficiency and improving overall performance. Researchers developing novel methods must select appropriate environments for evaluation and comparison with other methods. We introduce an overview of environments suitable for assessing curriculum learning methods, highlighting their key differences. This work details task components, modifications, and a classification of existing curriculum learning methods. We aim to provide researchers with valuable insights into the selection and utilization of environments for evaluating curriculum learning approaches.

自动课程学习的环境:一个简短的调查
强化学习包括各种方法,包括在多个任务上训练智能体。这些方法包括训练一个能够执行广泛任务的普通代理和训练一个专注于掌握特定技能的专门代理。课程学习战略性地安排任务,优化学习过程,提高培训效率,提高整体绩效。开发新方法的研究人员必须选择合适的环境进行评估和与其他方法的比较。我们概述了适合评估课程学习方法的环境,强调了它们的主要区别。这项工作详细介绍了任务的组成、修改和现有课程学习方法的分类。我们的目标是为研究人员提供有价值的见解,以选择和利用环境来评估课程学习方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Doklady Mathematics
Doklady Mathematics 数学-数学
CiteScore
1.00
自引率
16.70%
发文量
39
审稿时长
3-6 weeks
期刊介绍: Doklady Mathematics is a journal of the Presidium of the Russian Academy of Sciences. It contains English translations of papers published in Doklady Akademii Nauk (Proceedings of the Russian Academy of Sciences), which was founded in 1933 and is published 36 times a year. Doklady Mathematics includes the materials from the following areas: mathematics, mathematical physics, computer science, control theory, and computers. It publishes brief scientific reports on previously unpublished significant new research in mathematics and its applications. The main contributors to the journal are Members of the RAS, Corresponding Members of the RAS, and scientists from the former Soviet Union and other foreign countries. Among the contributors are the outstanding Russian mathematicians.
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