Towards Adjustable Autonomy for the Real World

by   D. V. Pynadath, et al.

Adjustable autonomy refers to entities dynamically varying their own autonomy, transferring decision-making control to other entities (typically agents transferring control to human users) in key situations. Determining whether and when such transfers-of-control should occur is arguably the fundamental research problem in adjustable autonomy. Previous work has investigated various approaches to addressing this problem but has often focused on individual agent-human interactions. Unfortunately, domains requiring collaboration between teams of agents and humans reveal two key shortcomings of these previous approaches. First, these approaches use rigid one-shot transfers of control that can result in unacceptable coordination failures in multiagent settings. Second, they ignore costs (e.g., in terms of time delays or effects on actions) to an agent's team due to such transfers-of-control. To remedy these problems, this article presents a novel approach to adjustable autonomy, based on the notion of a transfer-of-control strategy. A transfer-of-control strategy consists of a conditional sequence of two types of actions: (i) actions to transfer decision-making control (e.g., from an agent to a user or vice versa) and (ii) actions to change an agent's pre-specified coordination constraints with team members, aimed at minimizing miscoordination costs. The goal is for high-quality individual decisions to be made with minimal disruption to the coordination of the team. We present a mathematical model of transfer-of-control strategies. The model guides and informs the operationalization of the strategies using Markov Decision Processes, which select an optimal strategy, given an uncertain environment and costs to the individuals and teams. The approach has been carefully evaluated, including via its use in a real-world, deployed multi-agent system that assists a research group in its daily activities.


page 7

page 9


Impact of Heterogeneity and Risk Aversion on Task Allocation in Multi-Agent Teams

Cooperative multi-agent decision-making is a ubiquitous problem with man...

Adaptive Agent Architecture for Real-time Human-Agent Teaming

Teamwork is a set of interrelated reasoning, actions and behaviors of te...

Towards Flexible Teamwork

Many AI researchers are today striving to build agent teams for complex,...

Information and Multi-Sensor Coordination

The control and integration of distributed, multi-sensor perceptual syst...

From Motor Control to Team Play in Simulated Humanoid Football

Intelligent behaviour in the physical world exhibits structure at multip...

The cost of coordination can exceed the benefit of collaboration in performing complex tasks

Collective decision-making is ubiquitous when observing the behavior of ...

The Communicative Multiagent Team Decision Problem: Analyzing Teamwork Theories and Models

Despite the significant progress in multiagent teamwork, existing resear...