machine learning

This article covers the problem of developing a control system for non-player characters in a multiplayer RPG. Commercial projects in the field of videogames and RPG (Role-Playing Game) projects in particular seldom use machine learning models for the implementation of character behaviour. The most common approach is to use primitive preprogrammed rules, or to implement a finite state machine. Such approaches ruin the immersion of playing with real creatures, since various predefined rules make the characters predictable.

Machine learning algorithms play an important role in analyzing complex data in research across various fields.  In this paper, we employ multiple regression algorithms and statistical techniques to investigate the relationship between objective and subjective quality of life indicators and reveal the key factors affecting happiness at the international level based on data from the Human Development Index and the World Happiness Index covering the period from 2015 to 2021.  The Pearson correlation analysis showed that happiness is related to the HDI score and GNI per capita.  The best-perfo

One of the important problems that urban residents suffer from is Traffic Congestion.  It makes their life more stressful, it impacts several sides including the economy: by wasting time, fuel and productivity.  Moreover, the psychological and physical health.  That makes road authorities required to find solutions for reducing traffic congestion and guaranteeing security and safety on roads.  To this end, detecting road users in real-time allows for providing features and information about specific road points.  These last are useful for road managers and also for road users about congeste

Machine learning algorithms have become very frequently used in natural language processing, notably sentiment analysis, which helps determine the general feeling carried within a text.  Among these algorithms, Support Vector Machines have proven powerful classifiers especially in such a task, when their performance is assessed through accuracy score and f1-score.  However, they remain slow in terms of training, thus making exhaustive grid-search experimentations very time-consuming.  In this paper, we present an observed pattern in SVM's accuracy, and f1-score approximated with a Lagrange

Many food contamination incidents have occurred during the last decade which has proven the failure of the food supply chain management system to track the food, money, and information movement within the food supply chain.  Many models have been established. This paper presents the design and implementation of the new model providing real-time data acquisition, monitoring, and storing on a tamper-proof blockchain of the main food supply movement.

Since the first computer, researchers always try to simulate human behave.  For Chatbots, one of the first goals is to interact with the user like a human using Natural Language.  For Health chatbots, another goal is as much important: be able to provide the correct answer to the user request.  Over Years, many health chatbots have been developed for many fields such as cancer, diagnosis orientation, psychiatrics, etc.

The results of the analysis of algorithmic models of machine learning application to the freight transportation process are given in this paper. Analysis of existing research allowed discovering a range of advantages in the application of computational intelligence in logistic systems, including increasing the accuracy of forecasting, reduction of transport costs, increasing the efficiency of cargo delivery, risks reduction, and search for key performance factors. In the research process, the main directions of application of algorithmic models of machine learning were determined.

Transport is a key factor influencing greenhouse gas emissions. In relation to this, the issues and challenges facing the transport industry were presented. The issues of challenges for the transport industry related to the European Green Deal were discussed. It discussed how the transport system is critical for European companies and global supply chains. The issues related to the exposure of society to costs are presented: greenhouse gas emissions and pollution. The article deals with the issues of managing transport processes in an enterprise.

      Based on analysis of the Tech Summer for Teachers Bootcamp webinars for the educational community organized by the IT Company SoftServe, attention is focused on their interdisciplinary approach, in particular in the teaching of philosophical disciplines. Special attention was paid to the anthropological component in the field of information technologies, artificial intelligence, cybersecurity and virtual communication.