Toward Human - Multiagent Teams

One of the most fundamental challenges of building a human-multiagent team is adjustable autonomy, a process in which the control over team decisions is dynamically transferred between humans and agents. This thesis studies adjustable autonomy in the context of a human interacting with a team of agents and focuses on four issues that arise when addressing this team-level adjustable autonomy problem in real-time uncertain domains. Firstly, the humans and agents may differ significantly in their worldviews and their capabilities. This difference leads to inconsistencies in how humans and agents solve problems. Despite such inconsistencies, previous work has rigidly assumed the infallibility of human decisions. However, in some cases following the human’s decisions lead to worse human-multiagent team performance. Secondly, it is desirable for the team to manage the uncertainty of action durations and plan for the optimal action at any point in time. This is a crucial challenge to address given that these human-multiagent teams are working in real-time with strict deadlines combined with the particularly uncertain duration of actions that involve a human. Thirdly, the team needs to be able to plan for the optimal time to interrupt certain actions. This is due to the fact that actions may take an uncertain amount of time and the deadline is approaching. The human-multiagent team may benefit from attempting an action for a given amount of time and interrupting the action if it does not finish in order to try another action that has a higher expected reward. Fourthly, team-level adjustable autonomy