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A Unifying Framework for Formal Theories of Novelty [electronic resource] : Discussions, Guidelines, and Examples for Artificial Intelligence / edited by Terrance Boult, Walter Scheirer.

Contributor(s): Material type: TextSeries: Synthesis Lectures on Computer VisionPublisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edition: 1st ed. 2024Description: XV, 110 p. 35 illus., 33 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783031330544
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleLOC classification:
  • TA1634
Online resources:
Contents:
A Unifying Framework for Novelty -- Example Application of Framework: CartPole Domain -- Image Classification -- Novelty in Handwriting Recognition -- Visual Media Caption Domain -- Monopoly Multi-Agent Game Domain -- Related Work -- Prior Perspectives on Novelty and Conclusions.
In: Springer Nature eBookSummary: This book presents the first unified formalization for defining novelty across the span of machine learning, symbolic-reasoning, and control and planning-based systems. Dealing with novelty, things not previously seen by a system, is a critical issue for building vision-systems and general intelligent systems. The book presents examples of using this framework to define and evaluate in multiple domains including image recognition image-based open world learning, hand-writing and author analysis, CartPole Control, Image Captioning, and Monopoly. Chapters are written by well-known contributors to this new and emerging field. In addition, examples are provided from multiple areas, such as machine-learning based control problems, symbolic reasoning, and multi-player games. .
Item type: List(s) this item appears in: Titluri cărți electronice Springer Nature 2025 (10631 titluri)
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A Unifying Framework for Novelty -- Example Application of Framework: CartPole Domain -- Image Classification -- Novelty in Handwriting Recognition -- Visual Media Caption Domain -- Monopoly Multi-Agent Game Domain -- Related Work -- Prior Perspectives on Novelty and Conclusions.

This book presents the first unified formalization for defining novelty across the span of machine learning, symbolic-reasoning, and control and planning-based systems. Dealing with novelty, things not previously seen by a system, is a critical issue for building vision-systems and general intelligent systems. The book presents examples of using this framework to define and evaluate in multiple domains including image recognition image-based open world learning, hand-writing and author analysis, CartPole Control, Image Captioning, and Monopoly. Chapters are written by well-known contributors to this new and emerging field. In addition, examples are provided from multiple areas, such as machine-learning based control problems, symbolic reasoning, and multi-player games. .

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