Article
Mechanics
Armand Despons, Luca Peliti, David Lacoste
Summary: This paper presents an adaptive version of Kelly's horse model, where the gambler learns from past race results using Bayesian inference. The cost of this gambling strategy is characterized, and the difference between the growth rate of the gambler and the optimal growth rate, known as the gambler's regret, is analyzed in terms of asymptotic scaling. The study also explores the relationship between this adaptive strategy and the universal portfolio strategy, and proposes improved adaptive strategies that exploit the information contained in the bookmaker odds distribution.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2022)
Article
Computer Science, Information Systems
Gleb Dubosarskii, Serguei Primak
Summary: Research on anti-jamming games in VANETs using realistic driving models with quadratic power functions in utility functions. Mathematical methods used to find Nash equilibrium in single-channel and multi-channel scenarios. Comparison of reinforcement learning algorithms in static and dynamic scenarios without environment information.
Article
Computer Science, Hardware & Architecture
Aamina Akbar, Sobia Jangsher, Farrukh A. Bhatti
Summary: PD-NOMA leverages users' distinct channel gains for multiplexing different signals in a single resource block in power domain, resulting in higher spectral efficiency, improved user fairness, better cell-edge throughput, increased reliability and connectivity, and low latency.
Article
Pediatrics
Carme Alejandre, Patricia Corniero, Gemma Claret, Carlos Alaez, Elisabeth Esteban, Iolanda Jordan
Summary: The study demonstrates that escape room is a valuable educational game that enhances students’ knowledge of sepsis management and is perceived positively by the participants.
Article
Computer Science, Artificial Intelligence
Hiva Malekpour, Ashkan Hafezalkotob, Kaveh Khalili-Damghani
Summary: Dynamic scheduling using real-time data in manufacturing systems allows for quick response to unforeseen events, reducing costs and making-span while enhancing customer satisfaction. The study focuses on a multi-product production system, considering competition and bargaining strategies among customers. A simulation-optimization approach based on discrete-event simulation and Simulated annealing is employed to minimize makespan in workstations, showing significant reductions for all players.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Review
Environmental Sciences
Jozef Lisowski
Summary: This work presents a mathematical description of a process game for safe ship driving when encountering other ships. The study considers state and control constraint variables, as well as acceptable ship tactics. Multi-criteria optimization operations are developed as positional and matrix games, and algorithms for ship collision avoidance are verified through digital simulation using MATLAB/Simulink.
Review
Computer Science, Information Systems
J. Amutha, Sandeep Sharma, Sanjay Kumar Sharma
Summary: This study provides a brief overview of clustering in wireless sensor networks based on three different categories, covering various performance metrics and parameters, and discussing comparative assessment of key aspects.
COMPUTER SCIENCE REVIEW
(2021)
Article
Engineering, Aerospace
Xiaopeng Gong, Wanchun Chen, Zhongyuan Chen
Summary: Intelligent game strategies based on deep reinforcement learning are proposed to address the attack and defense game problem in the target-missile-defender three-body confrontation scenario. The strategies include an attack strategy for attacking missiles and an active defense strategy for the target/defender. Reinforcement learning algorithm is introduced to improve the training purposefulness, and the reward function design considers the action spaces and reward/punishment conditions of attack and defense confrontation. Simulation results show that the missile's attack strategy can maneuver according to the battlefield situation and successfully hit the target, while the active defense strategy enables the less capable target/defender to defend against missiles with superior maneuverability.
Article
Computer Science, Artificial Intelligence
Mai Kiguchi, Waddah Saeed, Imran Medi
Summary: Educational Technology (EdTech) is an industry that combines education and technological advancements. Digital game-based learning (DGBL) is a specific category within EdTech. This study proposes an approach for defining and predicting churn in DGBL by analyzing a dataset from a Japanese company. The results indicate the effectiveness of the approach in determining and predicting churn in DGBL.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Interdisciplinary Applications
Saurabh Patare, Sri Vanamalla Venkataraman
Summary: In competitive markets, firms need to develop strategies for quality production, product pricing, and marketing efforts to sustain competition. This research uses a supply chain game to model the competition between two substitutable product supply chains. The findings suggest that competition intensity among supply chains leads to an increase in product quality level. In addition, comparisons with centralized settings and monopolistic markets are conducted, and the impact of asymmetric information about manufacturers' cost for quality production is explored in the competition between supply chains.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Agronomy
Wenxiong Wang, Ziying Song, Wei Zhou, Yong Jiang, Yuan Sun
Summary: This study constructs an evolutionary game model between the government and enterprises to investigate the implementation effect of farmland consolidation in the public-private partnership (PPP) model. The empirical results indicate that the enterprises' farmland operating income is the key factor affecting behavioral choices. The incentive mechanism can influence the decision-making direction and speed of both the government and enterprises. Additionally, regulation costs and officials' desire for promotion play important roles in the government's strategic choices, while farmers' supervision level affects the strategies of both the government and enterprises.
Article
Energy & Fuels
Zhiyuan Chen, Tieli Wang, Yafei Mao
Summary: This paper establishes an evolutionary game model to analyze the impact of strategic choices of governments, enterprises, and households on the operational efficiency of DPV power plants, and provides recommendations for DPV promotion policies.
Article
Economics
Timothy Tay, Carolina Osorio
Summary: This paper explores the use of Bayesian optimization with Gaussian process models to solve high-dimensional transportation problems. It proposes formulations of the prior mean function and covariance function of the Gaussian process that enable incorporation of problem-specific transportation information. The method is validated with 1-D and 100-D functions and applied to a high-dimensional traffic signal control problem in New York City.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2022)
Article
Physics, Multidisciplinary
Lei Wang, Wenjiang Zhou, Haitao Xu, Liang Li, Lei Cai, Xianwei Zhou
Summary: With the continuous development of the 6G mobile network, combining Multi-Access Edge Computing (MEC) with artificial intelligence has become a potential solution to meet the new Quality of Service (QoS) requirements for computing-intensive and delay-sensitive onboard applications. The proposed task offloading decision mechanism aims to minimize overall task processing delay and energy consumption through cooperative game and deep reinforcement learning (DRL).
FRONTIERS IN PHYSICS
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Ranjith Tellis, Olga Starobinets, Michael Prokle, Usha Nandini Raghavan, Christopher Hall, Tammana Chugh, Ekin Koker, Siva Chaitanya Chaduvula, Christoph Wald, Sebastian Flacke
Summary: Identifying areas for workflow improvement and growth is crucial for an interventional radiology department to remain competitive. Traditional methods like Lean and Six Sigma help reduce waste, but achieving efficient workflow requires both strategic and tactical approaches. Using discrete event simulation and simulation-based optimization can effectively identify inefficiencies and improve workflow through what-if scenario testing.
JOURNAL OF DIGITAL IMAGING
(2021)
