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Proceedings ArticleDOI

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

TLDR
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.
Abstract
Though adjustable autonomy is hardly a new topic in agent systems, there has been a general lack of consensus on terminology and basic concepts. In this paper, we describe the multi-dimensional nature of adjustable autonomy and give examples of how various dimensions might be adjusted in order to enhance performance of human-agent teams. We then introduce Kaa (KAoS adjustable autonomy), which extends our 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. The current implementation of Kaa uses a combination of ontologies represented in OWL and influence-diagram-based decision-theoretic algorithms to determine what if any changes should be made in agent autonomy in a given context. We have demonstrated Kaa as part of ONR-sponsored research to improve naval de-mining operations through more effective human-robot interaction. A brief comparison among alternate approaches to adjustable autonomy is provided.

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Citations
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Journal ArticleDOI

Situations and Attitudes.

TL;DR: Barwise and Perry as discussed by the authors tackle the slippery subject of ''meaning, '' a subject that has long vexed linguists, language philosophers, and logicians, and they tackle it in this book.
Journal ArticleDOI

Coactive design: designing support for interdependence in joint activity

TL;DR: It is argued for a human-robot system model that supports interdependence through careful attention to requirements for observability, predictability, and directability, which is a useful approach for developers trying to understand how to translate high-level teamwork concepts into reusable control algorithms, interface elements, and behaviors that enable robots to fulfill their envisioned role as teammates.
Proceedings Article

Building strong semi-autonomous systems

TL;DR: The broad rationale for semi-autonomy is examined and basic properties of such systems are defined and various design choices in the development of semi-Autonomous systems and their implications on planning and execution are examined.
Book ChapterDOI

A Conceptual Model of Layered Adjustable Autonomy

TL;DR: This paper proposes another model of autonomy that conceptualizes autonomy as a spectrum, which is constructed in a layered structure of a multi-agent environment called Layered Adjustable Autonomy (LAA).
Journal ArticleDOI

Security Modeling of Autonomous Systems: A Survey

TL;DR: The historical evolution of autonomy, its approaches, and the current trends in related fields to build robust autonomous systems are reviewed to discuss the cybersecurity of these systems.
References
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Book

The Ecological Approach to Visual Perception

TL;DR: The relationship between Stimulation and Stimulus Information for visual perception is discussed in detail in this article, where the authors also present experimental evidence for direct perception of motion in the world and movement of the self.
Journal ArticleDOI

The psychology of everyday things

TL;DR: In this paper, the authors argue that even the smartest among us can feel inept as we fail to figure our which light switch or oven burner to turn on, or whether to push, pull, or slide a door.
Book

Situations and Attitudes

Jon Barwise, +1 more
TL;DR: Barwise and Perry as discussed by the authors tackle the slippery subject of "meaning, " a subject that has long vexed linguists, language philosophers, and logicians, and they tackle it in this book.
Journal ArticleDOI

Situations and Attitudes.

TL;DR: Barwise and Perry as discussed by the authors tackle the slippery subject of ''meaning, '' a subject that has long vexed linguists, language philosophers, and logicians, and they tackle it in this book.
Journal ArticleDOI

Influence Diagrams

TL;DR: Innuence diagrams are graphical models for structuring decision scenarios, particularly scenarios consisting of a predeened sequence of actions and observations, and the Bayesian network framework with nodes for decisions and utilities is extended.
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