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Teamwork in Cyberspace: Using TEAMCORE to Make Agents Team-Ready

TLDR
In complex, dynamic and uncertain environments extending from disaster rescue missions, to future battlefields, to monitoring and surveillance tasks, to virtual training environments, tofuture robotic space missions, intelligent agents will play a key role in information gathering and filtering, as well as in task planning and execution.
Abstract: 
In complex, dynamic and uncertain environments extending from disaster rescue missions, to future battlefields, to monitoring and surveillance tasks, to virtual training environments, to future robotic space missions, intelligent agents will play a key role in information gathering and filtering, as well as in task planning and execution. Although physically distributed on a variety of platforms, these agents will interact with information sources, network facilities, and other agents via cyberspace, in the form of the Internet, Intranet, the secure defense communication network, or other forms of cyberspace. Indeed, it now appears well accepted that cyberspace will be (if it is not already) populated by a vast number of such distributed, individual agents.

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Citations
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Journal ArticleDOI

Fly-by-agent: Controlling a pool of UAVs via a multi-agent system

TL;DR: The structure of the system is described and the re-organisation of the agents as the mission progresses is illustrated with an example and the importance of whole system issues and the integration and test cycle for getting AI techniques working and accepted in an application is described.
Proceedings ArticleDOI

Coordination in Human-Agent-Robot Teamwork

TL;DR: In this paper, the authors discuss some of the challenges and requirements for successful coordination, and briefly how they have used KAoS HART services framework to support coordination in a multi- team human-robot field exercise.
Proceedings ArticleDOI

Adjustable Autonomy in the Context of Coordination

TL;DR: This approach to interaction between a large number of UAVs and a small number of humans has three key components which allow us to leverage human expertise by giving them responsibility for key coordination decisions, without risks to the coordination due to slow responses.
Proceedings ArticleDOI

Kaa: policy-based explorations of a richer model for adjustable autonomy

TL;DR: Kaa (KAoS adjustable autonomy), which extends previous work on KAoS policy and domain services to provide a policy-based capability for adjustable autonomy based on this richer notion of adjustable autonomy, is introduced.
Book ChapterDOI

Toward trustworthy adjustable autonomy in KAoS

TL;DR: Some important dimensions relating to autonomy are described and examples of how these dimensions might be adjusted in order to enhance performance of human-agent teams are given.
References
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Book

The uses of argument

TL;DR: In this paper, the origins of epistemological theory are discussed and the layout of argument and modal arguments are discussed, as well as the history of working logic and idealised logic.
Book

Unified Theories of Cognition

TL;DR: In this paper, the authors propose a unified theory of cognition for the task of the Task of the Book Foundations of Cognitive Science Behaving Systems Knowledge Systems Representation Machines and Computation Symbols Architectures Intelligence Search and Problem Spaces Preparation and Deliberation Summary Human Cognitive Architecture The Human is a Symbol System System Levels The Time Scale of Human Action The Biological Band The Neural Circuit Level The Real-Time Constraint on Cognition The Cognitive Band The Level of Simple Operations The First Level of Composed Operations The Intendedly Rational Band Higher Bands: Social, Historical
Journal ArticleDOI

Collaborative plans for complex group action

TL;DR: A revised and expanded version of SharedPlans that reformulates Pollack's (1990) definition of individual plans to handle cases in which a single agent has only partial knowledge and has the features required by Bratman's (1992) account of shared cooperative activity.
Posted Content

Towards Flexible Teamwork

TL;DR: In STEAM, team members monitor the team's and individual members' performance, reorganizing the team as necessary, and decision-theoretic communication selectivity in STEAM ensures reduction in communication overheads of teamwork, with appropriate sensitivity to the environmental conditions.
Journal ArticleDOI

Towards flexible teamwork

TL;DR: In this paper, the authors present a general, implemented model of teamwork, called STEAM, which is based on agents' building up a (partial) hierarchy of joint intentions (this hierarchy is seen to parallel Grosz & Kraus's partial Shared-Plans, 1996).