Yucheng Dong – författare

This book brings together past experience, current work and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. DCAI 2020 is a forum to present applications of innovative techniques for studying and solving complex problems in artificial intelligence and computing areas. This year’s technical program will present both high quality and diversity, with contributions in well-established and evolving areas of research. Specifically, 83 papers were submitted to main track and special sessions, by authors from 26 different countries representing a truly “wide area network” of research activity. The DCAI’20 technical program has selected 35 papers and, as in past editions, it will be special issues in ranked journals. This symposium is organized by the University of L'Aquila (Italy). We would like to thank all the contributing authors, the members of the Program Committee and thesponsors (IBM, Armundia Group, EurAI, AEPIA, APPIA, CINI, OIT, UGR, HU, SCU, USAL, AIR Institute and UNIVAQ).

This book is intended for researchers and postgraduates who are interested in the consensus reaching process in group decision-making problems. After reading this book, readers will possess a number of valuable tools for building consensus with minimum adjustments in the context of group decision-making.

This book proposes a novel CWW model to personalize individual semantics in linguistic decision making, based on two new concepts: numerical scale and consistency-driven methodology. The numerical scale model provides a unified framework to connect different linguistic symbolic computational models for CWW, and the consistency-driven methodology customizes individuals’ semantics to support linguistic group decision making by setting personalized numerical scales. The book is a valuable resource for researchers and postgraduates who are interested in CWW in linguistic decision making.

This book is intended for researchers and postgraduates who are interested in the consensus reaching process in group decision-making problems. It puts forward new optimization-based decision support approaches to help decision-makers find roadmaps to consensus with minimum adjustments. Simulation experiments and comparison analysis are subsequently conducted to assess the validity of the proposal. After reading this book, readers will possess a number of valuable tools for building consensus with minimum adjustments in the context of group decision-making. Further, the proposed approach can effectively reduce costs in consensus building.​

This book provides a comprehensive perspective on the development of distributed linguistic representations in decision making, including the taxonomy of existing distributed linguistic representations, the key elements, and the classifications. It systematically investigates the formation of distributed linguistic representations and the methodology for the distributed linguistic information transformations and unifications, as well as the fusion and consensus reaching. This book studies the distributed linguistic information in MADM and the PIS-based applications of distributed linguistic information processing in decision making. Distributed linguistic representations are powerful tools for modelling the uncertainty and complexity of preference information in linguistic decision making. This book is written for researchers and postgraduates interested in linguistic decision making. Readers will find out lots of clear cues for distributed linguistic representations and distributed linguistic methodology to support decision making.

This book investigates the DeGroot model in social network contexts, and proposes the social network DeGroot (SNDG) model.