Cognitive Information Processing for Intelligent Computing and Deep Learning Applications

March 16th, 2015

CI2S Enterprise Content Admin

CALL FOR CHAPTER PROPOSALS

Proposals Submission Deadline: March 30, 2015

Cognitive Information Processing

for Intelligent Computing and Deep Learning Applications

A book edited by

Dr. Leonid Perlovsky (Harvard University, USA)

Dr. Gary Kuvich (Open Group Master Certified IT Architect, USA)

To be published by IGI Global: http://bit.ly/1BCu9uV

For release in the Advances in Computational Intelligence and Robotics Book Series

Series ISSN: 2327-0411

Submit a Chapter Proposal to this Book

Series Description

The Advances in Computational Intelligence and Robotics (ACIR) Book Series encourages scholarly discourse on all topics pertaining to evolutionary computing, artificial life, computational intelligence, machine learning, and robotics. ACIR presents the latest research being conducted on diverse topics in intelligence technologies with the goal of advancing knowledge and applications in this rapidly evolving field.

Introduction

Cognitive computing and deep learning are two rapidly developing spheres of information technology. The success or failure of cognitive systems is based on the degree of their intelligence, which in turn is based on the strength of their cognitive models. Such models provide much-needed context to recognition and decision making. However, to-date, the majority of research into cognitive computing has focused on the semantics of natural language and abstract logic, while the underlying biological structures of the greatest cognitive model in existence—the human mind—has not yet received much attention as such.

The cognitive model of the human brain operates upon a rationale more complex and meticulously-structured than even the most advanced of artificial models. However, by applying the tools used to study such artificial models—tools including systematic diagrams, semiotic analysis, hierarchical mapping, perceptual processing, and dynamic fuzzy logic—to the framework of human cognition itself, new and powerful insights may be generated, allowing for practical, actionable software implementation.

Objective

This book aims to describe current and relevant theoretical frameworks regarding the application of cognitive computing and deep learning principles to the study of human cognition. It is the hope of the editors that this material will provide a jumping-off point for the creation of more robust models of topology and knowledge-representation, capable of overcoming problems which have long vexed those at the forefront of artificial intelligence, including metaphor, analogy, and dynamic knowledge-synthesis.

Target Audience

The target audience of this book will be composed of professionals and researchers working in the fields of automation of software design and information architectures, robotics and unmanned vehicles, information processing, and knowledge management.

Recommended topics include, but are not limited to, the following:

Existing problems in Cognitive Computing and Deep Learning
Understanding as system model
System as a mathematical and informational concept
Order in the system, and its topological representation; from sets to systems
Topological diagrammatic knowledge representation; deep systematic cognitive models
Duality of system and concept on hierarchical levels of knowledge models
Concept as a node of knowledge network;
Synthesis of hierarchical knowledge networks; creating new concepts on fly
Concepts and their symbols; cognitive semiotics
Systems and their Patterns
Providing System Context for Accurate Pattern Recognition
Unified representation of percepts and concepts
Analogy, metaphors, and conceptual blending as structural topological operations
Logic and decision making in synthesis of topological system structure
Synthesis of new systematic knowledge structures on fly
Semantics as subset of semiotics
Interacting cognition and language in the hierarchy of semiotic models
Mechanisms that make cognitive system working: instinctual drives and emotions
Knowledge Instinct as driving mechanism for building deep cognitive models
Dynamic Logics as fundamental mechanism of deep learning, and its connections with Semiotics
Deep Systematic Models and Deep Learning; generating on fly dynamic diagrammatic models in universal semiotic format
Any topic related to diagrammatic representation, diagrammatic reasoning, and automated synthesis of diagrammatic models in any applied area or discipline

Submission Procedure

Researchers and practitioners are invited to submit on or before March 30, 2015, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by April 30, 2015 about the status of their proposals and sent chapter guidelines. Full chapters are expected to be submitted by June 30, 2015. All submitted chapters will be reviewed on a double-blind review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, Cognitive Information Processing for Intelligent Computing and Deep Learning Applications. All manuscripts are accepted based on a double-blind peer review editorial process.

All proposals should be submitted through the “Propose a Chapter” link at the bottom of this page.

Publisher

This book is scheduled to be published by IGI Global (formerly Idea Group Inc.), publisher of the “Information Science Reference” (formerly Idea Group Reference), “Medical Information Science Reference,” “Business Science Reference,” and “Engineering Science Reference” imprints. For additional information regarding the publisher, please visit www.igi-global.com. This publication is anticipated to be released in 2016.

Important Dates

March 30, 2015: Proposal Submission Deadline

April 30, 2015: Notification of Acceptance

June 30, 2015: Full Chapter Submission

August 31, 2015: Review Results Returned

October 15, 2015: Final Acceptance Notification

October 30, 2015: Final Chapter Submission

Inquiries may be directed to:

Dr. Leonid Perlovsky

Harvard University, Cambridge, MA, USA,

Tel.: +1 617-259-0197

E-mail: lperl@rcn.com