报告题目：Research Trends and Challenges on Large-Group Decision Making and Consensus Support
报告专家：Dr. Iván Palomares Carrascosa
邀 请 人：陈振颂
Decision-making is an inherent mankind process of ubiquitous nature in our daily lives. Real-life decision situations typically involve added complexities such as: (I) the need for effectively handling uncertainty stemming from human vagueness and subjectivity in expressing preferences; (II) the presence of multiple evaluation criteria and participants with diverse background, demanding appropriate preference aggregation methods; and importantly, (III) the importance of making highly accepted collective decisions in collective settings. All the above challenges accentuate in problems involving large, highly heterogeneous groups of decision makers. Large-group decision situations - in which participants may not necessarily be physically congregated - have increasingly become a reality in recent years, due to the rise of social network platforms and advances in mobile/cloud computing.
This talk firstly introduces some noteworthy challenges and limitations that arise in decision-making problems involving large groups, followed by a categorisation of existing solutions based on intelligent techniques. Secondly, recent works undertaken by the speaker are presented, particularly oriented towards consensus support, non-cooperative behaviour management and subgroup clustering approaches. Thirdly, ongoing work is presented in detail. The talk concludes with a series of “lessons learnt” and future directions of research.
Iván Palomares Carrascosa is an Assistant Professor in Computer Science with the School of Computer Science, Electrical and Electronic Engineering, and Engineering Maths (SCEEM), University of Bristol, and visiting Professor with the Management and Economics Sciences School, University of Occidente (Mexico). He received his MSc and PhD degrees (with nationwide distinctions) from the Universities of Granada and Jaén (Spain). Iván’s research interests include AI techniques to support decision making under uncertainty, consensus building, multi-view and collaborative filtering recommender systems, human-machine decision support, fuzzy preference aggregation and data fusion. Applications of his research include management, group recommender systems, disaster management, cybersecurity and energy planning. He has co-authored 13 publications in international journals and over 30 contributions to conferences, along with his recently published co-edited Springer book “Data Analytics and Decision Support for Cybersecurity”.