Journal ArticleDOI
Designs for explaining intelligent agents
TLDR
Designs that can be reused to create intelligent agents capable of explaining themselves are described and inscribe lessons learned from prior research and provide guidance for incorporating explanation facilities into intelligent systems.Abstract:
Explanation is an important capability for usable intelligent systems, including intelligent agents and cognitive models embedded within simulations and other decision support systems. Explanation facilities help users understand how and why an intelligent system possesses a given structure and set of behaviors. Prior research has resulted in a number of approaches to provide explanation capabilities and identified some significant challenges. We describe designs that can be reused to create intelligent agents capable of explaining themselves. The designs include ways to provide ontological, mechanistic, and operational explanations. These designs inscribe lessons learned from prior research and provide guidance for incorporating explanation facilities into intelligent systems. The designs are derived from both prior research on explanation tool design and from the empirical study reported here on the questions users ask when working with an intelligent system. We demonstrate the use of these designs through examples implemented using the Herbal high-level cognitive modeling language. These designs can help build better agents-they support creating more usable and more affordable intelligent agents by encapsulating prior knowledge about how to generate explanations in concise representations that can be instantiated or adapted by agent developers.read more
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Proceedings ArticleDOI
Trends and Trajectories for Explainable, Accountable and Intelligible Systems: An HCI Research Agenda
TL;DR: This work investigates how HCI researchers can help to develop accountable systems by performing a literature analysis of 289 core papers on explanations and explaina-ble systems, as well as 12,412 citing papers.
Posted Content
A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems
TL;DR: A framework with step-by-step design guidelines paired with evaluation methods to close the iterative design and evaluation cycles in multidisciplinary XAI teams is developed and summarized ready-to-use tables of evaluation methods and recommendations for different goals in XAI research are provided.
Proceedings Article
Explainable Agents and Robots: Results from a Systematic Literature Review
TL;DR: A Systematic Literature Review of eXplainable Artificial Intelligence (XAI), finding that almost all of the studied papers deal with robots/agents explaining their behaviors to the human users, and very few works addressed inter-robot (inter-agent) explainability.
Posted Content
Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI.
TL;DR: The Report expresses the explainability issues and challenges in modern AI, and presents capsule views of the leading psychological theories of explanation, and encourages AI/XAI researchers to include in their research reports fuller details on their empirical or experimental methods.
Journal ArticleDOI
Notions of explainability and evaluation approaches for explainable artificial intelligence
Giulia Vilone,Luca Longo +1 more
TL;DR: This systematic review contributes to the body of knowledge by clustering all the scientific studies via a hierarchical system that classifies theories and notions related to the concept of explainability and the evaluation approaches for XAI methods.
References
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Design Patterns: Elements of Reusable Object-Oriented Software
TL;DR: The book is an introduction to the idea of design patterns in software engineering, and a catalog of twenty-three common patterns, which most experienced OOP designers will find out they've known about patterns all along.
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The Intentional Stance
TL;DR: The Intentional Stance as discussed by the authors is the first full-scale presentation of a theory of intentionality that has been developed for almost twenty years, and it can be seen as a pre-emptive strategy of interpretation that presupposes the rationality of the people or other entities we are hoping to understand and predict.
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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