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Maximal coverage problems with routing constraints using cross-entropy Monte Carlo tree search
Spatial search, and environmental monitoring are key technologies in robotics. These problems can be reformulated as maximal coverage problems with...
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Ciphertext-policy attribute-based encryption with hidden sensitive policy from keyword search techniques in smart city
Countless data generated in Smart city may contain private and sensitive information and should be protected from unauthorized users. The data can be...
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Secure Keyword Search over Encrypted Cloud Data Using Blockchain in Digital Document Sharing
Due to the drawbacks of the many-to-many search model for accessing digital records in institutional settings like offices, hospitals, and government...
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FuseBot: mechanical search of rigid and deformable objects via multi-modal perception
Mechanical search is a robotic problem where a robot needs to retrieve a target item that is partially or fully-occluded from its camera....
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Stochastic Kriging-Based Optimization Applied in Direct Policy Search for Decision Problems in Infrastructure Planning
In this paper, we apply a stochastic Kriging-based optimization algorithm to solve a generic infrastructure planning problem using direct policy...
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Distributed Multi-agent Target Search and Tracking With Gaussian Process and Reinforcement Learning
Deploying multiple robots for target search and tracking has many practical applications, yet the challenge of planning over unknown or partially...
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Monte Carlo tree search control scheme for multibody dynamics applications
There is considerable interest in applying reinforcement learning (RL) to improve machine control across multiple industries, and the automotive...
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Robot Search Path Planning Method Based on Prioritized Deep Reinforcement Learning
The path planning process of the robot relies too much on environmental information, which makes it difficult to obtain the optimal search path when...
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Relabeling and policy distillation of hierarchical reinforcement learning
Hierarchical reinforcement learning (HRL) is a promising method to extend traditional reinforcement learning to solve more complex tasks. HRL can...
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Bandit neural architecture search based on performance evaluation for operation selection
Neural architecture search (NAS) plays an important role in many computer vision tasks. However, the high computational cost of forward and backward...
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A tailored adaptive large neighborhood search algorithm for the air cargo partitioning problem with a piecewise linear cost function
Motivated by a leading Chinese multinational manufacturer’s practical air cargo logistics activities, we investigate an air cargo partitioning...
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Policy gradients using variational quantum circuits
Variational quantum circuits are being used as versatile quantum machine learning models. Some empirical results exhibit an advantage in supervised...
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Reinforcement Learning for Expert Finding from Web Search Results
Finding experts is a crucial problem for develo** countries, since these highly qualified expatriates might be able to contribute to the local...
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An Extensive Application of Model Predictive Control Combined with Policy Search to Multi-agent Agile UAV Flight
Reinforcement Learning (RL) methods can automatically learn complex policies with minimum prior knowledge about the task. Meanwhile, Model Predictive...
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A model for fresh produce with inflation induced dynamic demand under dynamic trade credit policy in imprecise environments
The significance of product freshness is heightened by the health-conscious market and the current circumstances. The quality of the product declines...
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Priority fractional rationing (PFR) policy and a hybrid metaheuristic for managing stock in divergent supply chains
A distributor catering to demands of multiple retailers is considered in this paper and stock-management in this divergent supply chain is achieved...
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Redis-based full-text search extensions for relational databases
In order to overcome the inefficiency and resource consumption of full-text search in relational databases, a light full-text search model with...
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Gait Learning Reproduction for Quadruped Robots Based on Experience Evolution Proximal Policy Optimization
Bionic gait learning of quadruped robots based on reinforcement learning has become a hot research topic. The proximal policy optimization (PPO)...
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Analysis of Markovian Retrial Queue with Double Orbits, Vacation, Orbital Search, and Disaster Using ANFIS Approach
This article deals with Markovian queueing model for the service system in which orbital search and system disaster are presumed. In queueing...
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A condition-based maintenance policy for reconfigurable multi-device systems
The exploration of component states for optimizing maintenance schedules in complex systems has garnered significant interest from researchers....
