Search Results for author: Daoyi Dong

Found 15 papers, 4 papers with code

Path Planning for Cellular-Connected UAV: A DRL Solution with Quantum-Inspired Experience Replay

no code implementations30 Aug 2021 Yuanjian Li, A. Hamid Aghvami, Daoyi Dong

In cellular-connected unmanned aerial vehicle (UAV) network, a minimization problem on the weighted sum of time cost and expected outage duration is considered.

Rule-Based Reinforcement Learning for Efficient Robot Navigation with Space Reduction

no code implementations15 Apr 2021 Yuanyang Zhu, Zhi Wang, Chunlin Chen, Daoyi Dong

In this paper, we focus on efficient navigation with the RL technique and combine the advantages of these two kinds of methods into a rule-based RL (RuRL) algorithm for reducing the sample complexity and cost of time.

Robot Navigation

Bayesian adversarial multi-node bandit for optimal smart grid protection against cyber attacks

no code implementations20 Feb 2021 Jianyu Xu, Bin Liu, Huadong Mo, Daoyi Dong

The cybersecurity of smart grids has become one of key problems in developing reliable modern power and energy systems.

Deep Reinforcement Learning with Quantum-inspired Experience Replay

no code implementations6 Jan 2021 Qing Wei, Hailan Ma, Chunlin Chen, Daoyi Dong

In this paper, a novel training paradigm inspired by quantum computation is proposed for deep reinforcement learning (DRL) with experience replay.

Atari Games

Expectation Synchronization Synthesis in Non-Markovian Open Quantum Systems

no code implementations4 Jan 2021 Shikun Zhang, Kun Liu, Daoyi Dong, Xiaoxue Feng, Feng Pan

In this article, we investigate the problem of engineering synchronization in non-Markovian quantum systems.

Quantum Physics

Curriculum-based Deep Reinforcement Learning for Quantum Control

no code implementations31 Dec 2020 Hailan Ma, Daoyi Dong, Steven X. Ding, Chunlin Chen

Deep reinforcement learning has been recognized as an efficient technique to design optimal strategies for different complex systems without prior knowledge of the control landscape.

Instance Weighted Incremental Evolution Strategies for Reinforcement Learning in Dynamic Environments

1 code implementation9 Oct 2020 Zhi Wang, Chunlin Chen, Daoyi Dong

Instance novelty measures an instance's difference from the previous optimum in the original environment, while instance quality corresponds to how well an instance performs in the new environment.

Incremental Learning Q-Learning +1

Quantum Language Model with Entanglement Embedding for Question Answering

no code implementations23 Aug 2020 Yi-Wei Chen, Yu Pan, Daoyi Dong

Quantum Language Models (QLMs) in which words are modelled as quantum superposition of sememes have demonstrated a high level of model transparency and good post-hoc interpretability.

Language Modelling Question Answering

Lifelong Incremental Reinforcement Learning with Online Bayesian Inference

1 code implementation28 Jul 2020 Zhi Wang, Chunlin Chen, Daoyi Dong

In this paper, we propose LifeLong Incremental Reinforcement Learning (LLIRL), a new incremental algorithm for efficient lifelong adaptation to dynamic environments.

Bayesian Inference

Intelligent Trajectory Planning in UAV-mounted Wireless Networks: A Quantum-Inspired Reinforcement Learning Perspective

no code implementations27 Jul 2020 Yuanjian Li, A. Hamid Aghvami, Daoyi Dong

In this paper, we consider a wireless uplink transmission scenario in which an unmanned aerial vehicle (UAV) serves as an aerial base station collecting data from ground users.

Trajectory Planning

On compression rate of quantum autoencoders: Control design, numerical and experimental realization

no code implementations22 May 2020 Hailan Ma, Chang-Jiang Huang, Chunlin Chen, Daoyi Dong, Yuanlong Wang, Re-Bing Wu, Guo-Yong Xiang

Quantum autoencoders which aim at compressing quantum information in a low-dimensional latent space lie in the heart of automatic data compression in the field of quantum information.

Data Compression

Fidelity-based Probabilistic Q-learning for Control of Quantum Systems

no code implementations8 Jun 2018 Chunlin Chen, Daoyi Dong, Han-Xiong Li, Jian Chu, Tzyh-Jong Tarn

In this paper, a fidelity-based probabilistic Q-learning (FPQL) approach is presented to naturally solve this problem and applied for learning control of quantum systems.

Q-Learning

Learning-based Quantum Robust Control: Algorithm, Applications and Experiments

no code implementations13 Feb 2017 Daoyi Dong, Xi Xing, Hailan Ma, Chunlin Chen, Zhixin Liu, Herschel Rabitz

Numerical results are presented to demonstrate the excellent performance of the improved machine learning algorithm for these two classes of quantum robust control problems.

Quantum reinforcement learning

2 code implementations21 Oct 2008 Daoyi Dong, Chunlin Chen, Hanxiong Li, Tzyh-Jong Tarn

The state (action) set can be represented with a quantum superposition state and the eigen state (eigen action) can be obtained by randomly observing the simulated quantum state according to the collapse postulate of quantum measurement.

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