[1]Arora S, Doshi P. A survey of inverse reinforcement learning: Challenges, methods and progress[J]. Artificial Intelligence, 2021: 103500. [2]A. Ng, S. Russell, Algorithms for inverse reinforcement learning, Proceedings of the Seventeenth International Conference on Machine Learning 0 (2000) ...
Learning from demonstration, or imitation learning, is the process of learning to act in an environment from examples provided by a teacher. Inverse reinforcement learning (IRL) is a specific form of learning from demonstration that attempts to estimate the reward function of a Markov decision proce...
Learning from demonstration, or imitation learning, is the process of learning to act in an environment from examples provided by a teacher. Inverse reinforcement learning (IRL) is a specific form of learning from demonstration that attempts to estimate the reward func- tion of a Markov decision ...
A survey of inverse reinforcement learning: Challenges, methods and progresspdf.sciencedirectassets.com/271585/1-s2.0-S0004370221X00057/1-s2.0-S0004370221000515/main.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjEHMaCXVzLWVhc3QtMSJHMEUCIF37wdDVr0aSPl%2Bl13tRyje3PKNG9MKU8qBotCupdFulAiEAuJOZVjd...
Inverse reinforcement learning is the problem of inferring the reward function of an observed agent, given its policy or behavior. Researchers perceive IRL both as a problem and as a class of methods. By categorically surveying the current literature in IRL, this article serves as a reference for...
内容提示: Apprenticeship Learning via Inverse Reinforcement LearningPieter Abbeel pabbeel@cs.stanford.eduAndrew Y. Ng ang@cs.stanford.eduComputer Science Department, Stanford University, Stanford, CA 94305, USAAbstractWe consider learning in a Markov decisionprocess where we are not explicitly given a ...
A major obstacle to the realization of novel inorganic materials with desirable properties is efficient materials discovery over both the materials property and synthesis spaces. In this work, we propose and compare two novel reinforcement learning (RL)
Keywords: deep learning; inverse design; nanobeams; nanolasers; photonic crystals; reinforcement learning 1 Introduction Inverse design of optical resonators [1, 2] is a crucial step in designing state-of-the-art nanoscale laser cavities [3] that realize classic photonic crystal lasers [4–6] fin...
Driving behavior modeling using naturalistic human driving data with inverse reinforcement learning. IEEE Trans. Intell. Transp. Syst. 2021. [Google Scholar] [CrossRef] Le Mero, L.; Yi, D.; Dianati, M.; Mouzakitis, A. A survey on imitation learning techniques for end-to-end autonomous ...
Does inverse scaling persist forInstructGPT modelstrained withReinforcement Learning from Human Feedback (RLHF)? To test this, you can usethe same code as that for GPT-3 evaluation. We may also evaluate submissions on private RLHF models of various sizes from Anthropic [Bai et al. 2022]. ...