Human-AI Collaborative Approaches to Supporting Multi-stage, Stochastic Multi-criteria Decision Making

The Hong Kong University of Science and Technology
Department of Computer Science and Engineering


PhD Thesis Defence


Title: "Human-AI Collaborative Approaches to Supporting Multi-stage, Stochastic
Multi-criteria Decision Making"

By

Miss Chuhan SHI


Abstract:

Multi-stage, stochastic multi-criteria decision making (MSMDM) is common in
various domains of human activity, such as scientific research and
combinatorial games. These decision tasks involve a series of interdependent
decision-making stages where options are evaluated based on multiple criteria
under uncertainty and variability. Since MSMDM is challenging for decision
makers, a number of AI-powered methods have emerged to facilitate MSMDM.
However, these methods have inherent limitations, e.g., dependence on training
datasets and lack of transparency, especially on complex decision tasks.
Therefore, we propose to explore Human-AI (HAI) collaboration approaches for
MSMDM. Specifically, this thesis consists of three pieces of work, studying
different HAI collaboration approaches and investigating critical issues for
representative MSMDM tasks. First, we take the task of deciding research
directions in medicinal chemistry as our target problem and propose
MedChemLens, an interactive visual system to support users to explore the built
decision spaces and make decisions based on their various criteria. It takes an
AI-assisted decision-making approach by automatically extracting and organizing
molecular features from scholarly publications and visualizing the practicality
of associated experiments. Second, we design RetroLens, an HAI collaborative
system, which integrates two HAI collaboration methods to facilitate multi-step
retrosynthetic route planning in synthetic chemistry. RetroLens adopts a joint
action method to help chemists construct the decision spaces for retrosynthetic
route planning together with AI and then utilizes AI-assisted decisionmaking to
facilitate multi-criteria route revision, empowering personalized decision path
exploration. Third, we focus on Go game playing and present a method,
HandoverLens. This methods quantifies the potential benefit and cost of
assigning each decision making stage to human or AI to promote effective HAI
collaboration in simultaneously constructing decision spaces and exploring
decision paths of Go playing. In all, these three pieces demonstrate the
feasibility of our proposed HAI collaborative approaches to supporting MSMDM.


Date:                   Wednesday, 23 August 2023

Time:                   3:00pm - 5:00pm

Venue:                  Room 4475
                        lifts 25/26

Chairperson:            Prof. Hai YANG (CIVL)

Committee Members:      Prof. Qiong LUO (Supervisor)
                        Prof. Xiaojuan MA (Supervisor)
                        Prof. Qifeng CHEN
                        Prof. Huamin QU
                        Prof. Haibin SU (CHEM)
                        Prof. Li CHEN (HKBU)


**** ALL are Welcome ****