Thông báo tham dự buổi seminar với chủ đề "Optimization in Human-Agent Collectives"
Ngày 06 tháng 01 năm 2017, Khoa CNTT sẽ tổ chức buổi Seminar với chủ đề "Optimization in Human-Agent Collectives" do Tiến sĩ Long Tran-Thanh (Assistant Professor) đến từ Đại học Southampton trình bày.
Thông tin buổi seminar:
- Chủ đề: Optimization in Human-Agent Collectives
- Thời gian: 14:00 ngày 06 tháng 01 năm 2017
- Địa điểm: Phòng họp C
Sau đây là thông tin về buổi seminar và một vài sơ lược về Tiến sĩ Long Tran-Thanh.
Due to the recent development of novel technologies such as Internet of Things (IoT), autonomous machines (e.g., driverless cars, or UAVs), and crowdsourcing systems, collaborative AI systems, or human-agent collectives (as called by some other researchers), in which humans and machines (or agents) have to perform some degree of cooperation with each other in order to achieve certain goals, are becoming a reality. In many cases, the required objectives of these collectives can be formalized as optimization problems. However, standard optimisation solution techniques fail to efficiently tackle these objectives, as they typically ignore the optimization constraints caused by the human factor. For example, algorithms that require a sequence of iterative optimization steps (e.g., gradient descent) assume that the participating agent (or human) will follow the steps of the optimisation process, described by the algorithm. However, humans might get disengaged or unmotivated, and thus, might leave the process, or intentionally do not follow the instructions given by the algorithm. Another example comes from the potential miscommunication between humans and agents, typically caused by inefficient interaction interfaces. Finally, trust (e.g., is the human trustworthy?), privacy (e.g., how to protect the human’s privacy?), and security (e.g., how not to provide security wholes with humans typically to be the weakest chain) issues might occur during the process. Such new constraints introduce new challenges in solving optimization problems of human-agent collectives. Whereas some solutions have been proposed to tackle specific sub-problems with restricted settings, no effort has been made to date to investigate the problems of user motivation, privacy and security from a more fundamental and generic perspective, which is essential in order to fully understand these problems, and thus, to provide more efficient solutions to tackle them. In this talk, I will discuss some research solutions within each abovementioned topic. In particular, I will mainly focus on the problem of having the human factor in optimization problems, a research area I have been working on with my collaborators from the University of Southampton, Nanyang Technical University, and University of Southern California.
Long is a Hungarian-Vietnamese computer scientist at the University of Southampton, UK, where he is a Lecturer in Computer Science. Long did his university studies in Budapest, Hungary (BME-VIK) and obtained his PhD from Southampton in 2012, under the supervision of Nick Jennings and Alex Rogers. He has been doing active research in a number of key areas of AI, mainly focusing on online machine learning, game theory, and incentive engineering. For his work, he has received a number of prestigious awards, such as:
(i) the CPHC/BCS PhD Dissertation Award (for the best Computer Science PhD thesis in the UK in 2012/2013) - Honourable Mention;
(ii) the ECCAI Artificial Intelligence Dissertation Award (for the best European PhD thesis in AI in 2012) - Honourable Mention;
(iii) the Association for the Advancement of Artificial Intelligence (AAAI) Outstanding Paper 2012 Award - Honourable Mention; and
(iv) the European Conference on Artificial Intelligence (ECAI) Best Student Paper 2012 Award - Runner-Up.