دانلود کتاب هوش مصنوعی و مدیریت پروژه

The popularity and importance of various types of projects are constantly growing in the face of the increasing complexity of the functioning of mod¬ern organizations. They often take up the challenge of giving up relatively simple, repetitive, and process-based work organization in favor of focusing on unique and complex projects, the implementation of which means making decisions in conditions of uncertainty.
In practice, uncertain decisions related to the planning and implementa¬tion of projects are made using multicriteria expert analysis. This means that companies often need to rely on experts’ tacit and subjective knowledge. Apart from that, project management and evaluation issues are poorly struc¬tured decision-making problems in conditions of high uncertainty. It results from the increasing complexity of many external and internal conditions of the organization’s functioning, as well as the significant variability and turbulence of the project environment. The need to analyze, in conditions of considerable uncertainty, complex and complicated phenomena that occur in a dynamically changing environment forces the use of solutions based on nondeterministic models and artificial intelligence (AI) algorithms.
Although some people had considerable doubts about the usefulness of such solutions in the past, AI plays a growing role in modern business. The dynamic development of new technologies and rich applications of AI and knowledge-based systems (KBS) in business and management indicates that they also cre¬ate a significant potential for changes in supporting the planning, evaluation, and performance of a wide range of temporary, unique, and complex endeavors. It can be expected that the interest in them will also lead to an increase in sup¬port for the planning, evaluation, and implementation of projects. In particular, the proper functioning of multifaceted evaluation methods has a crucial impact on the appropriate planning and execution of various projects, as well as the effective achievement of the organization’s goals.
Knowledge-based evaluation may be one of the directions for developing comprehensive approaches and methods, the implementation of which may con¬tribute to the improvement of the quality, effectiveness, and objectivity of project planning, evaluation, and execution processes. The value of this book results from a synthetic presentation of complex problems and challenges related to the devel¬opment of AI in project management, proposing an integrated approach to knowl¬edge-based evaluation, and indicating the possibilities of improving professional practical knowledge in this field. The book outlines the general background of such issues, the chosen basic concepts, and the general usefulness of selected AI methods in project management. Its content is intended to encourage familiarity with and use of the proposed integrated approach to knowledge-based evaluation.
Various methods supporting project management and evaluation are of interest to business practitioners and consultants. Classic tools and techniques for assessing investment projects based on quantitative financial indicators are well developed. However, there is a growing interest on the part of prac¬titioners in a scientific solution to the problem of multifaceted evaluation of contemporary sustainable projects (organizational, strategic, social, environ¬mental, etc.), which often requires considering hard-to-quantify phenomena and qualitative criteria. These practitioners understand the limitations of long-standing classic tools and methods in supporting decisions for advanced projects. The impact of scientific research in this field can be supplemented thanks to the proposed solutions based on the extensive achievements in improved information and communications technology (ICT) solutions, data science methods, and machine learning (ML).
The content presented in this book is useful outside the university environment due to the practical usefulness of solutions considering quantitative financial cri¬teria and other qualitative and difficult-to-measure economic, social, environmen¬tal, and sustainable development aspects. Research on the use of AI in this area is at an early stage of development. This book briefly describes one of the more interesting research trends related to knowledge-based evaluation.