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- Title
Variational Quantum Circuit-Based Reinforcement Learning for POMDP and Experimental Implementation.
- Authors
Kimura, Tomoaki; Shiba, Kodai; Chen, Chih-Chieh; Sogabe, Masaru; Sakamoto, Katsuyoshi; Sogabe, Tomah
- Abstract
Variational quantum circuit is proposed for applications in supervised learning and reinforcement learning to harness potential quantum advantage. However, many practical applications in robotics and time-series analysis are in partially observable environment. In this work, we propose an algorithm based on variational quantum circuits for reinforcement learning under partially observable environment. Simulations suggest learning advantage over several classical counterparts. The learned parameters are then tested on IBMQ systems to demonstrate the applicability of our approach for real-machine-based predictions.
- Subjects
SUPERVISED learning; REINFORCEMENT learning; TIME series analysis; TEST systems
- Publication
Mathematical Problems in Engineering, 2021, p1
- ISSN
1024-123X
- Publication type
Article
- DOI
10.1155/2021/3511029