Unified Computational Intelligence For Complex Systems
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Unified Computational Intelligence For Complex Systems
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Author : John Seiffertt
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-07-15
Unified Computational Intelligence For Complex Systems written by John Seiffertt and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-15 with Computers categories.
Computational intelligence encompasses a wide variety of techniques that allow computation to learn, to adapt, and to seek. That is, they may be designed to learn information without explicit programming regarding the nature of the content to be retained, they may be imbued with the functionality to adapt to maintain their course within a complex and unpredictably changing environment, and they may help us seek out truths about our own dynamics and lives through their inclusion in complex system modeling. These capabilities place our ability to compute in a category apart from our ability to erect suspension bridges, although both are products of technological advancement and reflect an increased understanding of our world. In this book, we show how to unify aspects of learning and adaptation within the computational intelligence framework. While a number of algorithms exist that fall under the umbrella of computational intelligence, with new ones added every year, all of them focus on the capabilities of learning, adapting, and helping us seek. So, the term unified computational intelligence relates not to the individual algorithms but to the underlying goals driving them. This book focuses on the computational intelligence areas of neural networks and dynamic programming, showing how to unify aspects of these areas to create new, more powerful, computational intelligence architectures to apply to new problem domains.
Unified Computational Intelligence For Complex Systems
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Author : John Seiffertt
language : en
Publisher: Springer
Release Date : 2011-07-23
Unified Computational Intelligence For Complex Systems written by John Seiffertt and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-23 with Computers categories.
Computational intelligence encompasses a wide variety of techniques that allow computation to learn, to adapt, and to seek. That is, they may be designed to learn information without explicit programming regarding the nature of the content to be retained, they may be imbued with the functionality to adapt to maintain their course within a complex and unpredictably changing environment, and they may help us seek out truths about our own dynamics and lives through their inclusion in complex system modeling. These capabilities place our ability to compute in a category apart from our ability to erect suspension bridges, although both are products of technological advancement and reflect an increased understanding of our world. In this book, we show how to unify aspects of learning and adaptation within the computational intelligence framework. While a number of algorithms exist that fall under the umbrella of computational intelligence, with new ones added every year, all of them focus on the capabilities of learning, adapting, and helping us seek. So, the term unified computational intelligence relates not to the individual algorithms but to the underlying goals driving them. This book focuses on the computational intelligence areas of neural networks and dynamic programming, showing how to unify aspects of these areas to create new, more powerful, computational intelligence architectures to apply to new problem domains.
Axionomics
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Author : Ronald Legarski
language : en
Publisher: SolveForce
Release Date : 2025-02-24
Axionomics written by Ronald Legarski and has been published by SolveForce this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-24 with Philosophy categories.
Axionomics presents a comprehensive, recursive framework that unifies axiomatic principles, atomic structures, quantum mechanics, and decentralized knowledge systems into a self-regulating, axiom-driven knowledge and energy economy. By integrating linguistic organization, artificial intelligence (AI), blockchain-backed verification, and decentralized scientific governance, this revolutionary model creates a seamless bridge between foundational principles and applied systems. Operating simultaneously across quantum, atomic, and macroscopic organizational scales, Axionomics leverages recursive feedback loops and self-referential processes to enable continuous adaptation and optimization. This dynamic, self-evolving architecture refines itself in response to new discoveries while preserving core axiomatic integrity, ensuring the stability of knowledge structures even in rapidly advancing scientific fields. By fostering interdisciplinary collaboration, Axionomics reshapes scientific inquiry, computational intelligence, and organizational governance. This system transcends conventional limitations, offering a self-optimizing knowledge ecosystem that harmonizes theory and practice, unlocking new frontiers in innovation, knowledge distribution, and decentralized intelligence networks. As a transformative model, Axionomics redefines how we understand, verify, and apply knowledge, setting the foundation for a future driven by recursive intelligence, axiomatic reasoning, and sustainable progress.
Algonomics
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Author : Ronald Legarski
language : en
Publisher: SolveForce
Release Date : 2025-03-02
Algonomics written by Ronald Legarski and has been published by SolveForce this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-02 with Computers categories.
At its core, Algonomics represents a revolutionary approach to understanding, structuring, and governing algorithmic systems. By offering a unified theoretical foundation for computational processes, it establishes a recursive, structured framework that transcends traditional algorithmic models, integrating linguistic, computational, quantum, and systemic logic principles into a self-regulating intelligence system. Unlike algorithmics, which focuses primarily on procedural computation, Algonomics extends beyond conventional models, creating a recursive, self-optimizing intelligence framework that structures and adapts computational logic across systemic architectures. By ensuring structured logical integrity, interdisciplinary computational standardization, and self-sustaining systemic automation, Algonomics enables efficient and scalable knowledge integration across diverse fields of study, including artificial intelligence, quantum computing, cryptography, and network optimization. The term "Algonomics" originates from "Algo-" (Latinized from Arabic al-Khwarizmi, referencing systematic calculation) and "-nomics" (Greek nomos, meaning law or system). This etymological foundation reflects its purpose as a recursive framework for algorithms and computational logic across disciplines. Algonomic networks in action reveal how interconnected algorithmic processes form a dynamic flow of information, reinforcing recursive computational frameworks. By visualizing recursive patterns in computation, Algonomics demonstrates the elegant complexity of algorithmic governance, ensuring efficient, adaptive, and self-optimizing systemic structures. Through this recursive approach, Algonomics transforms computational logic into a self-regulating mechanism that governs data processing, decision-making, and machine intelligence at unprecedented levels.
Handbook Of Swarm Intelligence
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Author : Bijaya Ketan Panigrahi
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-02-04
Handbook Of Swarm Intelligence written by Bijaya Ketan Panigrahi and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-02-04 with Computers categories.
From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more. It is only in recent years that researchers have taken notice of such natural swarming systems as culmination of some form of innate collective intelligence, albeit swarm intelligence (SI) - a metaphor that inspires a myriad of computational problem-solving techniques. In computational intelligence, swarm-like algorithms have been successfully applied to solve many real-world problems in engineering and sciences. This handbook volume serves as a useful foundational as well as consolidatory state-of-art collection of articles in the field from various researchers around the globe. It has a rich collection of contributions pertaining to the theoretical and empirical study of single and multi-objective variants of swarm intelligence based algorithms like particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization algorithm (BFOA), honey bee social foraging algorithms, and harmony search (HS). With chapters describing various applications of SI techniques in real-world engineering problems, this handbook can be a valuable resource for researchers and practitioners, giving an in-depth flavor of what SI is capable of achieving.
Human Centred Intelligent Systems
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Author : Alfred Zimmermann
language : en
Publisher: Springer Nature
Release Date : 2021-05-28
Human Centred Intelligent Systems written by Alfred Zimmermann and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-28 with Technology & Engineering categories.
This book highlights new trends and challenges in intelligent systems, which play an essential part in the digital transformation of many areas of science and practice. It includes papers offering a deeper understanding of the human-centred perspective on artificial intelligence, of intelligent value co-creation, ethics, value-oriented digital models, transparency, and intelligent digital architectures and engineering to support digital services and intelligent systems, the transformation of structures in digital business and intelligent systems based on human practices, as well as the study of interaction and co-adaptation of humans and systems. All papers were originally presented at the International KES Conference on Human Centred Intelligent Systems 2021 (KES HCIS 2021) held on June 14–16, 2021 in the KES Virtual Conference Centre.
Reinforcement Learning
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Author : Marco Wiering
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-03-05
Reinforcement Learning written by Marco Wiering and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-05 with Computers categories.
Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents. As a field, reinforcement learning has progressed tremendously in the past decade. The main goal of this book is to present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning. This includes surveys on partially observable environments, hierarchical task decompositions, relational knowledge representation and predictive state representations. Furthermore, topics such as transfer, evolutionary methods and continuous spaces in reinforcement learning are surveyed. In addition, several chapters review reinforcement learning methods in robotics, in games, and in computational neuroscience. In total seventeen different subfields are presented by mostly young experts in those areas, and together they truly represent a state-of-the-art of current reinforcement learning research. Marco Wiering works at the artificial intelligence department of the University of Groningen in the Netherlands. He has published extensively on various reinforcement learning topics. Martijn van Otterlo works in the cognitive artificial intelligence group at the Radboud University Nijmegen in The Netherlands. He has mainly focused on expressive knowledge representation in reinforcement learning settings.
Integrative Bioinformatics For Biomedical Big Data
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Author : Xiuzhen Huang
language : en
Publisher: Cambridge University Press
Release Date : 2023-09-28
Integrative Bioinformatics For Biomedical Big Data written by Xiuzhen Huang and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-28 with Science categories.
Explains the value of no-boundary thinking (NBT) in biological and biomedical research in helping to define impactful research questions.
Embedded Automation In Human Agent Environment
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Author : Jeff Tweedale
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-09-25
Embedded Automation In Human Agent Environment written by Jeff Tweedale and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-25 with Computers categories.
This research book proposes a general conceptual framework for the development of automation in human-agents environments that will allow human- agent teams to work effectively and efficiently. We examine various schemes to implement artificial intelligence techniques in agents. The text is directed to the scientists, application engineers, professors and students of all disciplines, interested in the agency methodology and applications.
Onomics
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Author : Ronald Legarski
language : en
Publisher: SolveForce
Release Date : 2025-02-27
Onomics written by Ronald Legarski and has been published by SolveForce this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-27 with Language Arts & Disciplines categories.
Onomics represents a groundbreaking paradigm shift in how human knowledge is structured, integrated, and understood. By establishing a meta-framework that transcends traditional academic boundaries, Onomics unifies mathematical principles, linguistic structures, quantum mechanics, and philosophical axioms into a single, coherent model of understanding. This recursive, self-regulating approach allows us to map the interconnections between different domains of knowledge, ensuring logical consistency and empirical validity across all scales of analysis. Rooted in its etymology—"O-" (being, existence) and "-nomics" (law, system)—Onomics serves as the fundamental framework governing all knowledge, integrating language, atomic structures, quantum mechanics, and axiomatic reasoning into an indivisible model of universal intelligence. At its core, Onomics synthesizes: Axionomics → The Axiomatic Foundations of Universal Knowledge Isonomics → The Equilibrium and Isomorphic Correspondence Between Systems Lanomics → The Linguistic Singularity as the Only Absolute Truth Atonomics → Atomic Structures as the Fundamental Building Blocks of Reality Omninomics → The Unification of Sciences, Mathematics, and Language into a Recursive Model Omniomics → The Universal Knowledge Singularity By leveraging: AI-powered reasoning models – Ensuring recursive knowledge validation and epistemological integrity Quantum interconnectivity modeling – Establishing the dynamic relationships between knowledge structures Recursive interdisciplinary optimization – Refining knowledge structures through continuous feedback loops Atomic-to-linguistic standardization – Harmonizing physical and informational realities into a single framework Onomics establishes a self-sustaining, balance-driven model where structured reasoning, atomic stability, and interdisciplinary terminology unify physics, mathematics, quantum mechanics, and linguistic coherence. As a recursive, all-encompassing system, Onomics reconciles all systems into a unified totality, providing a new era of knowledge organization, scientific integration, and epistemological standardization.