Dimensions of Adjustable Autonomy

Barber, K. Suzanne; Martin, Cheryl; Reed, Nancy E.; Kortenkamp, David

doi:10.1007/3-540-45408-x_36

Cited by 7 publications

(5 citation statements)

References 4 publications

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“…Researchers around the world have carried much research into the evaluation of unmanned systems, each having their own clear application objectives [6][7][8][9][10][11][12][40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55]. The level of research interest in China on this topic has slowly risen, with existing research mainly having focused on introducing, analyzing, and tracking foreign research; Chinese research is thus still in its infancy [21][22][23][24][25]27,28,30,32,33,37,38].…”

Section: Survey Of Current Evaluation Methodsmentioning

confidence: 99%

Evaluation methods for the autonomy of unmanned systems

Wang

Liu

2012

Chin. Sci. Bull.

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Future military and civilian unmanned systems will be extensively used on land, under the sea, in air, and in space. Evaluation of their autonomy is critical to realize the autonomous operation ability of unmanned systems. This paper discussed the basic concepts of autonomy and the significance of autonomy evaluation, and then surveys and describes existing evaluating methods. Based on analyses of key technologies and these technologies' technical readiness levels, a cobweb evaluation model as a universal evaluation model has been used to evaluate unmanned systems. If the technology warps (aspects of autonomy) and wefts (levels of those aspects) of unmanned systems can be determined for the cobweb model, the model can handle the mutual coupling, high dimensions, and diversity of warp lines. This model potentially has wide application in evaluating various unmanned systems.

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Section: Survey Of Current Evaluation Methodsmentioning

confidence: 99%

Evaluation methods for the autonomy of unmanned systems

Wang

Liu

2012

Chin. Sci. Bull.

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“…Therefore, various researchers investigating adjustable autonomy are considering the issue from various different viewpoints. Recently, several researchers investigating adjustable autonomy collaborated to describe the various dimensions of adjustable autonomy being explored and relate them to one another [7].…”

Section: Adjustable Autonomymentioning

confidence: 99%

Adaptive decision-making frameworks for dynamic multi-agent organizational change

Martin

Barber

2006

Auton Agent Multi-Agent Syst

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This article presents a capability called Adaptive Decision-Making Frameworks (ADMF) and shows that it can result in significantly improved system performance across run-time situation changes in a multi-agent system. Specifically, ADMF can result in improved and more robust performance compared to the use of a single static decision-making framework (DMF). The ADMF capability allows agents to dynamically adapt the DMF in which they participate to fit their run-time situation as it changes. A DMF identifies a set of agents and specifies the distribution of decisionmaking control and the authority to assign subtasks among these agents as they determine how a goal or set of goals should be achieved. The ADMF capability is a form of organizational adaptation and differs from previous approaches to organizational adaptation and dynamic coordination in that it is the first to allow dynamic and explicit manipulation of these DMF characteristics at run-time as variables controlling agent behavior. The approach proposed for selecting DMFs at run-time parameterizes all domain-specific knowledge as characteristics of the agents' situation, so the approach is application-independent. The presented evaluation empirically shows that, for at least one multi-agent system, there is no one best DMF for multiple agents across run-time situational changes. Next, it motivates the further exploration of ADMF by showing that adapting DMFs to run-time variations in situation can result in improved overall system performance compared to static or random DMFs.

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“…The dimensions of agent autonomy and adjustable autonomy continue to be explored (Barber et al, 2001;Castelfranchi, 1995;Hexmoor, 2001;Luck and d'Inverno, 2001). Although no common view of agent autonomy has been reached in the research community, the exploration of these concepts has helped us better understand the complex relationship between humans and autonomous agents.…”

Section: Related Workmentioning

confidence: 99%

Supporting group interaction among humans and autonomous agents

Schreckenghost¹,

Martin²,

Bonasso³

et al. 2002

Connection Science

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An important aspect of interaction among groups of humans and software agents is supporting collaboration among these heterogeneous agents while they operate remotely and communicate asynchronously. We are developing an architecture that supports multiple humans interacting with multiple automated control agents in such a manner. We are evaluating this architecture with a group consisting of the crew of a space-based vehicle and the automated software agents controlling the vehicle systems. Such agent interaction is modeled as a loosely coordinated group because this model minimizes agent commitment to group goals and constraints while addressing a significant portion of crew and control agent group behaviors. In this paper we give background on human interaction with space-based automation. We identify related research in multi-agent autonomous architectures and single agent human-computer interaction systems. We describe our architecture design for human-software agent groups. And we identify research issues in loosely coordinated human-software groups.

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Dimensions of Adjustable Autonomy

Cited by 7 publications

References 4 publications

Evaluation methods for the autonomy of unmanned systems

Evaluation methods for the autonomy of unmanned systems

Adaptive decision-making frameworks for dynamic multi-agent organizational change

Supporting group interaction among humans and autonomous agents

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