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Data-efficient model-based reinforcement learning with trajectory discrimination
Deep reinforcement learning has always been used to solve high-dimensional complex sequential decision problems. However, one of the biggest...
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Model-based deep reinforcement learning for accelerated learning from flow simulations
In recent years, deep reinforcement learning has emerged as a technique to solve closed-loop flow control problems. Employing simulation-based...
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Study on force control for robot massage with a model-based reinforcement learning algorithm
When a robot end-effector contacts human skin, it is difficult to adjust the contact force autonomously in an unknown environment. Therefore, a robot...
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Reinforcement learning with model-based feedforward inputs for robotic table tennis
We rethink the traditional reinforcement learning approach, which is based on optimizing over feedback policies, and propose a new framework that...
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Efficient hyperparameters optimization through model-based reinforcement learning with experience exploiting and meta-learning
Hyperparameter optimization plays a significant role in the overall performance of machine learning algorithms. However, the computational cost of...
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Deep Reinforcement Learning with Inverse Jacobian based Model-Free Path Planning for Deburring in Complex Industrial Environment
In this study, we present an innovative approach to robotic deburring path planning by combining deep reinforcement learning (DRL) with an inverse...
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Node selection for model quality optimization in hierarchical federated learning based on deep reinforcement learning
In Hierarchical Federated Learning (HFL), data sample sizes and distribution of different clients vary greatly. Due to the heterogeneity of the data,...
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Model Predictive Adaptive Cruise Control of Intelligent Electric Vehicles Based on Deep Reinforcement Learning Algorithm FWOR Driver Characteristics
This paper presents a novel model predictive adaptive cruise control strategy of intelligent electric vehicles based on deep reinforcement learning...
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Autonomous Navigation Using Model-Based Reinforcement Learning
Autonomous driving does not yet have an industry-standard approach. One of the currently promising approaches is reinforcement learning. A novel...
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Reinforcement Learning Optimal Feedback Control with Industrial Applications
This book offers a thorough introduction to the basics and scientific and technological innovations involved in the modern study of...
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Safe Exploration in Model-Based Reinforcement Learning
In this chapter, we show how to use reinforcement learning (RL) to generate a control policy for the same uncertain dynamical system considered in...
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A Procedural Constructive Learning Mechanism with Deep Reinforcement Learning for Cognitive Agents
Recent advancements in AI and deep learning have created a growing demand for artificial agents capable of performing tasks within increasingly...
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A Deep Reinforcement Learning Real-Time Recommendation Model Based on Long and Short-Term Preference
With the development of Internet technology, the problem of information overload has increasingly attracted attention. Nowadays, the recommendation...
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Addressing Task Prioritization in Model-based Reinforcement Learning
World models facilitate sample-efficient reinforcement learning (RL) and, by design, can benefit from the multitask information. However, it is not...
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A Reinforcement Learning-Based Portfolio Return Prediction Model
Maximizing returns is always people’s investment goal. Gold and bitcoin have some hedging ability, and their prices fluctuate greatly, making them...
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UAV Head-On Situation Maneuver Generation Using Transfer-Learning-Based Deep Reinforcement Learning
Recently, the demand for unmanned aerial vehicle technology has increased. In particular, AI pilots through reinforcement learning (RL) are more...
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A reinforcement learning approach for thermostat setpoint preference learning
Occupant-centric controls (OCC) is an indoor climate control approach whereby occupant feedback is used in the sequence of operation of building...
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Digital Continuity Based on Reinforcement Learning Model Transformations
With the importance gained by Service-Oriented Architectures (SOA) to simplify and decompose complex enterprise information system into autonomous,...
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Maximum diffusion reinforcement learning
Robots and animals both experience the world through their bodies and senses. Their embodiment constrains their experiences, ensuring that they...
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Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning
As models based on machine learning continue to be developed for healthcare applications, greater effort is needed to ensure that these technologies...
