報(bào)告人：Iván Palomares Carrascosa博士 英國Bristol大學(xué)
報(bào)告題目：Identifying
the challenges of making consensual large-group decisions under fuzziness (模糊環(huán)境下大規(guī)模一致性群決策所面臨的挑戰(zhàn))
報(bào)告時(shí)間：2018年4月3日（星期二）09:30-10:15
報(bào)告地點(diǎn)：九里校區(qū)4號教學(xué)樓J4322
報(bào)告內(nèi)容簡介：
Real-life
collective decision making typically involves added complexities such as: (I)
the need for handling uncertainty due to human vagueness/subjectivity in
expressing opinions; (II) the presence of participants with diverse background,
requiring appropriate opinion aggregation methods; and importantly, (III) the
importance of making consensual decisions. All the above challenges accentuate
in large-group decision making problems involving tens to thousands of highly
diverse participants. Large-group decisions have increasingly become a reality
in recent years, due to the rise of social networks, crowd-based platforms, and
the latest advances in mobile/cloud computing.
The aim of
this talk is to identify main challenges that arise in conventional group
decision-making models in the literature, to handle large-group decision making
problems. A particular focus is given to consensus approaches to support
accepted large-group decisions so that dissension across participants is
alleviated as much as possible. The potential relationship between this area of
research and major computer science trends (including data science and
artificial intelligence techniques) along with other disciplines, is
highlighted.
報(bào)告人簡介：
Iván
Palomares Carrascosa is a Lecturer in Data Science and Artificial Intelligence
with the School of Computer Science, Electrical and Electronic Engineering, and
Engineering Maths (SCEEM), University of Bristol. He is the academic lead of
the “Decision Support and Recommender Systems” research theme, within Bristol’s
Intelligent Systems Lab. Iván 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 complex decision making under
uncertainty, consensus building, recommender systems, human-machine decision
support, fuzzy preference aggregation and data fusion. Applications of his
research include management, group and multi-view recommender systems, disaster
management, cybersecurity and energy planning. He has co-authored 15
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” and his first own authored
book “Large Group Decision Making” to be available soon (mid-2018).
