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Principles of Noology

Part of the Socio-Affective Computing Book Series (volume 3)

DOI: 10.1007/978-3-319-32113-4

ISBN: 978-3-319-32111-0

Publisher: Springer International Publishing - Springer Journals

Jun 29, 2016

1 - 10 of 10 Chapters

Available

Introduction

Ho, Seng-Beng

Pages: 1 –39

[This introductory chapter provides an overview of the principled and fundamental theoretical framework developed in this book to characterize intelligent systems, or “noological systems.” Firstly, a set of fundamental principles is stated that lies at the core of noological systems. Then, a...
Available

Rapid Unsupervised Effective Causal Learning

Ho, Seng-Beng

Pages: 41 –87

[This chapter introduces a novel learning paradigm that underpins the rapid learning ability of noological systems – effective causal learning. The learning process is rapid, requiring only a handful of training instances. The causal rules learned are instrumental in problem solving, which is the...
Available

A General Noological Framework

Ho, Seng-Beng

Pages: 89 –144

[A number of issues are discussed in this chapter that build on previous discussions toward the characterization of a general noological framework. Spatial movement is used as an example to discuss the connection between the needs and motivations of a noological system and its attendant...
Available

Conceptual Grounding and Operational Representation

Ho, Seng-Beng

Pages: 145 –189

[Conceptual grounding refers to the process of linking concepts represented in a noological system to its real-world referents. This imbues the system with the ability to “truly understand” the concepts that it manipulates and enables it to apply them for problem solving and other noological...
Available

Causal Rules, Problem Solving, and Operational Representation

Ho, Seng-Beng

Pages: 191 –219

[Building on the conceptual grounding framework set up by the previous chapter, this chapter illustrates the application of grounded operational representations for the formulation of causal rules. Causal rules are noologically efficacious entities that enable effective problem solving. Causal...
Available

The Causal Role of Sensory Information

Ho, Seng-Beng

Pages: 221 –282

[This chapter investigates in a deep and principled manner how sensory information contributes to a noological system’s learning and formulation of causal rules that enables it to solve problems rapidly and effectively. The spatial movement to goal with obstacle problem is used to illustrate this...
Available

Application to the StarCraft Game Environment

Ho, Seng-Beng

Pages: 283 –342

[The StarCraft game environment provides an ideal computational platform to test and illustrate the various principles of noology that have been described in the previous chapters. In this chapter we describe an implemented AI program that plays against the StarCraft built-in game engine. Causal...
Available

A Grand Challenge for Noology and Computational Intelligence

Ho, Seng-Beng

Pages: 343 –357

[In this chapter, a carefully designed micro-environment, called the Shield-and-Shelter (SAS) micro-environment, is described as a benchmark for adaptive autonomous intelligent agents (AAIA). This benchmark specifies what an AAIA needs to be able to do to be considered fully adaptive and...
Available

Affect Driven Noological Processes

Ho, Seng-Beng

Pages: 359 –389

[In this chapter, a partial solution to the grand challenge posed in the previous chapter is presented. Again, all the noological processing devices that were developed earlier are brought to bear on the problem, notably those from Chaps. 6 and 7. This further affirms that the devices developed...
Available

Summary and Beyond

Ho, Seng-Beng

Pages: 391 –418

[In this chapter, other than summarizing the achievement of this book, a number of important issues are discussed. These include the issue of scaling – how can the principles and methodologies developed in this book be scaled up to handle the real-world environment, both internal and external to...

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