A Multiagent System for Solving the Activity Selection and Scheduling Coordination Problem

Deadline pressures, unexpected events, and combinatorial numbers of possible courses of action often lead a person to decide which activity she will begin next without considering a full enumeration of possible schedules, and thus, without a full awareness of the implications that her choice will have on the rest of her day's schedule. Furthermore, people suffering from cognitive impairments may lack the abilities to perform such reasoning in the first place. The goal of my thesis is to develop foundational technologies for computational agents that augment the abilities of people who face the above challenges to reason about the implications of scheduling. In particular, I develop, integrate, and evaluate new techniques for solving multi-agent Hybrid Scheduling Problems, which support coordinated activity selection and scheduling for human users.