Decentralized partially observable Markov decision processes (Dec-POMDPs) are general multi-agent models for planning under uncertainty, but are intractable to solve. Doubly exponential growth of the search space as the horizon increases makes a brut...
In this study, we develop new Hermite–Hadamard and Hermite–Hadamard–Fejér type inequalities for fuzzy interval-valued functions (FIVFs) that exhibit h-Godunova–Levin convexity, using the framework of the Riemann–L...
This study presents a comparison between the results of process parameter optimization for the deep drawing of an AA5754-O automotive fuel tank, which utilizes two different objective functions. The first objective function is the maximum thinning pe...
The interval-valued q-rung dual hesitant linguistic (IVq-RDHL) sets are widely used to express the evaluation information of decision makers (DMs) in the process of multi-attribute decision-making (MADM). However, the existing MADM method based on IV...
This paper studies a class of integral boundary value problem of fractional q-difference equations. We first give an explicit expression for the associated Green’s function and obtain an important property of the function. The new property allo...
Background/Objectives: Pancreatic symptoms and structural abnormalities do not necessarily correspond to reduced exocrine function in type 2 diabetes mellitus (T2DM). We aimed to estimate the frequency of reduced fecal elastase-1 (FE-1) and examine i...
In a multi-agent system, the complex interaction among agents is one of the difficulties in making the optimal decision. This paper proposes a new action value function and a learning mechanism based on the optimal equivalent action of the neighborho...
We consider a train scheduling problem in which both local and express trains are to be scheduled. In this type of train scheduling problem, the key decision is determining the overtaking stations at which express trains overtake their preceding loca...
This study presents the first investigation into the problem of autonomous vehicle (AV) merging into existing platoons, proposing a multi-agent deep reinforcement learning (MA-DRL)-based cooperative control framework. The developed MA-DRL architectur...
The cumulative distribution function of the non-central chi-square distribution
In this paper, the theoretical stability of batch offline action-dependent heuristic dynamic programming (BOADHDP) is analyzed for deep neural network (NN) approximators for both the action value function and controller which are iteratively improved...
Q-learning has been primarily used as one of the reinforcement learning (RL) techniques to find the optimal routing path in wireless sensor networks (WSNs). However, for the centralized RL-based routing protocols with a large state space and action s...
We investigated the reaction Q-value (
In this paper, the notions of post-quantum integrals for two-variable interval-valued functions are presented. The newly described integrals are then used to prove some new Hermite–Hadamard inclusions for co-ordinated convex interval-valued functions...
Software-defined networking (SDN) has become one of the critical technologies for data center networks, as it can improve network performance from a global perspective using artificial intelligence algorithms. Due to the strong decision-making and ge...
Ground autonomous mobile robots are increasingly critical for reconnaissance, patrol, and resupply tasks in public safety and national defense scenarios, where global path planning in 3D uneven terrains remains a major challenge. Traditional planners...
Model-free reinforcement learning is a powerful and efficient machine-learning paradigm which has been generally used in the robotic control domain. In the reinforcement learning setting, the value function method learns policies by maximizing the st...
A multi-agent system (MAS) is suitable for addressing tasks in a variety of domains without any programmed behaviors, which makes it ideal for the problems associated with the mobile robots. Reinforcement learning (RL) is a successful approach used i...
Compared to model-based Reinforcement Learning (RL) approaches, model-free RL algorithms, such as Q-learning, require less space and are more expressive, since specifying value functions or policies is more flexible than specifying the model for the...
Underwater Wireless Sensor Networks (UWSNs) have aroused increasing interest of many researchers in industry, military, commerce and academe recently. Due to the harsh underwater environment, energy efficiency is a significant theme should be conside...
Devices used in Internet of Things (IoT) networks continue to perform sensing, gathering, modifying, and forwarding data. Since IoT networks have a lot of participants, mitigating and reducing collisions among the participants becomes an essential re...
Background: Our objective was to identify and validate proteins that predict which patients with ovarian cancer will respond to SHetA2, an investigational drug in a phase 1 trial for patients with advanced or recurrent solid tumors (clinicaltrials.go...
The contradiction between economic growth and carbon emissions restricts the sustainable development of developing countries. Whether territorial spatial functional conflicts (TSFCs) are statistically associated with the intensification of this tensi...
In existing phased-array radar systems, anti-jamming strategies are mainly generated through manual judgment. However, manually designing or selecting anti-jamming decisions is often difficult and unreliable in complex jamming environments. Therefore...
This research study represents a polydexterous deep reinforcement learning-based pick-and-place framework for industrial clutter scenarios. In the proposed framework, the agent tends to learn the pick-and-place of regularly and irregularly shaped obj...
An in-depth understanding of the spatiotemporal heterogeneity of ecosystem service (ES) trade-offs and synergies, along with their driving factors, is crucial for formulating key ecological restoration strategies and effectively allocating ecological...
Urban vitality provides a human-activity-based lens for evaluating how existing urban land supports everyday use and is therefore relevant to sustainable urban regeneration in compact cities. This study examines block-level activity patterns and thei...
In emergency rescue missions, rescue teams can use UAVs and efficient path planning strategies to provide flexible rescue services for trapped people, which can improve rescue efficiency and reduce personnel risks. However, since the task environment...
Differentiation and variation in body color has been a growing limitation to the commercial value of red tilapia. Limited microRNA (miRNA) information is available on skin color differentiation and variation in fish so far. In this study, a high-thro...
The statistics of grain displacements probability distribution function (pdf) during the shear of a granular medium displays an unusual dependence with the shear increment upscaling as recently evinced (see “experimental validation of a nonexte...
Increasing evidence suggests a role of epigenetic mechanisms at chromosome 8q24, an important cancer genetic susceptibility region, in prostate cancer. We investigated whether MYC DNA methylation at 8q24 (six CpG sites from exon 3 to the 3′ UTR...
Optimizing long-term user satisfaction in sequential recommender systems is a critical challenge. Offline reinforcement learning (RL) offers a promising solution by learning recommendation policies from historical interaction logs without incurring t...
The multi-valued dependency matrix (MVD matrix) is an important testability modeling approach, which can deliver more comprehensive testability information than the traditional dependency matrix (D-matrix). However, existing testability strategy opti...
The key module for autonomous mobile robots is path planning and obstacle avoidance. Global path planning based on known maps has been effectively achieved. Local path planning in unknown dynamic environments is still very challenging due to the lack...
Biochar has significant potential for livestock microbiomes and crop agriculture regarding greenhouse gas emissions reduction. Therefore, a pilot study was designed to investigate the effect of biochar application on the surface of swine manure from...
Path planning is the most fundamental necessity for autonomous mobile robots. Traditionally, the path planning problem was solved using analytical methods, but these methods need perfect localization in the environment, a fully developed map to plan...
This paper proposes a deep reinforcement learning (DRL)-based algorithm in the path-tracking controller of an unmanned vehicle to autonomously learn the path-tracking capability of the vehicle by interacting with the CARLA environment. To solve the p...
Deep reinforcement learning (DRL) trains agents to make decisions by learning from rewards and penalties, using trial and error. It combines reinforcement learning (RL) with deep neural networks (DNNs), enabling agents to process large datasets and l...
Mdx mice with a spontaneous mutation in exon 23 of the Dmd gene represent the most common model to investigate the pathophysiology of Duchenne muscular dystrophy (DMD). The disease, caused by the lack of functional dystrophin, is characterized by irr...
Despite advances in our knowledge and attempts to improve therapies, β-thalassemia remains a prevalent disorder with increased risk for the development of cardiomyopathy. Using an untargeted discovery-based lipidomic workflow, we uncovered that trans...
The main gearbox is very important for the operation safety of helicopters, and the oil temperature reflects the health degree of the gearbox; therefore establishing an accurate oil temperature forecasting model is an important step for reliable faul...
With the emergence of various types of applications such as delay-sensitive applications, future communication networks are expected to be increasingly complex and dynamic. Network Function Virtualization (NFV) provides the necessary support towards...
Effective real-time autonomous navigation for mobile robots in static and dynamic environments has become a challenging and active research topic. Although the simultaneous localization and mapping (SLAM) algorithm offers a solution, it often heavily...
Leukocyte telomere length (LTL) has been proposed as a molecular marker of biological aging reflecting cumulative cellular stress and replicative senescence. Multimorbidity represents a major challenge in aging populations and reflects the progressiv...
In goats, the influence of microRNAs on the post-transcriptional regulation of genes involved in mammary development and remodeling and milk secretion has not been fully elucidated yet. In this study, we have obtained mammary biopsies from five lacta...
Growth performance is an important economic trait in chicken. MicroRNAs (miRNAs) have been shown to play important roles in various biological processes, but their functions in chicken growth are not yet clear. To investigate the function of miRNAs...
In this study, morphology observation and illumina sequencing were performed on two different coloration skins of crimson snapper (Lutjanus erythropterus), the black zone and the red zone. Three types of chromatophores, melanophores, iridophores and...
This paper provides comprehensive insights into the cornea and its diseases, with a particular focus on keratoconus. This paper explores the cornea’s function in maintaining ocular health, detailing its anatomy, pathological conditions, and the...
In edge networks, hardware failures and resource pressure may disrupt Service Function Chains (SFCs) deployed on the failed node, making it necessary to efficiently migrate multiple Virtual Network Functions (VNFs) under limited resources. To address...
When compared to modern lean-type breeds, Portuguese local Alentejano (AL) and Bísaro (BI) pig breeds present a high potential for subcutaneous and intramuscular fat (IMF) deposition which contributes for better meat quality. The aim of this w...
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