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Author: Gianluca Baldassarre Publisher: Springer Science & Business Media ISBN: 3642398758 Category : Computers Languages : en Pages : 358
Book Description
Current robots and other artificial systems are typically able to accomplish only one single task. Overcoming this limitation requires the development of control architectures and learning algorithms that can support the acquisition and deployment of several different skills, which in turn seems to require a modular and hierarchical organization. In this way, different modules can acquire different skills without catastrophic interference, and higher-level components of the system can solve complex tasks by exploiting the skills encapsulated in the lower-level modules. While machine learning and robotics recognize the fundamental importance of the hierarchical organization of behavior for building robots that scale up to solve complex tasks, research in psychology and neuroscience shows increasing evidence that modularity and hierarchy are pivotal organization principles of behavior and of the brain. They might even lead to the cumulative acquisition of an ever-increasing number of skills, which seems to be a characteristic of mammals, and humans in particular. This book is a comprehensive overview of the state of the art on the modeling of the hierarchical organization of behavior in animals, and on its exploitation in robot controllers. The book perspective is highly interdisciplinary, featuring models belonging to all relevant areas, including machine learning, robotics, neural networks, and computational modeling in psychology and neuroscience. The book chapters review the authors' most recent contributions to the investigation of hierarchical behavior, and highlight the open questions and most promising research directions. As the contributing authors are among the pioneers carrying out fundamental work on this topic, the book covers the most important and topical issues in the field from a computationally informed, theoretically oriented perspective. The book will be of benefit to academic and industrial researchers and graduate students in related disciplines.
Author: Gianluca Baldassarre Publisher: Springer Science & Business Media ISBN: 3642398758 Category : Computers Languages : en Pages : 358
Book Description
Current robots and other artificial systems are typically able to accomplish only one single task. Overcoming this limitation requires the development of control architectures and learning algorithms that can support the acquisition and deployment of several different skills, which in turn seems to require a modular and hierarchical organization. In this way, different modules can acquire different skills without catastrophic interference, and higher-level components of the system can solve complex tasks by exploiting the skills encapsulated in the lower-level modules. While machine learning and robotics recognize the fundamental importance of the hierarchical organization of behavior for building robots that scale up to solve complex tasks, research in psychology and neuroscience shows increasing evidence that modularity and hierarchy are pivotal organization principles of behavior and of the brain. They might even lead to the cumulative acquisition of an ever-increasing number of skills, which seems to be a characteristic of mammals, and humans in particular. This book is a comprehensive overview of the state of the art on the modeling of the hierarchical organization of behavior in animals, and on its exploitation in robot controllers. The book perspective is highly interdisciplinary, featuring models belonging to all relevant areas, including machine learning, robotics, neural networks, and computational modeling in psychology and neuroscience. The book chapters review the authors' most recent contributions to the investigation of hierarchical behavior, and highlight the open questions and most promising research directions. As the contributing authors are among the pioneers carrying out fundamental work on this topic, the book covers the most important and topical issues in the field from a computationally informed, theoretically oriented perspective. The book will be of benefit to academic and industrial researchers and graduate students in related disciplines.
Author: Alexei V. Samsonovich Publisher: Springer ISBN: 331999316X Category : Technology & Engineering Languages : en Pages : 377
Book Description
The book focuses on original approaches intended to support the development of biologically inspired cognitive architectures. It bridges together different disciplines, from classical artificial intelligence to linguistics, from neuro- and social sciences to design and creativity, among others. The chapters, based on contributions presented at the Ninth Annual Meeting of the BICA Society, held in on August 23-24, 2018, in Prague, Czech Republic, discuss emerging methods, theories and ideas towards the realization of general-purpose humanlike artificial intelligence or fostering a better understanding of the ways the human mind works. All in all, the book provides engineers, mathematicians, psychologists, computer scientists and other experts with a timely snapshot of recent research and a source of inspiration for future developments in the broadly intended areas of artificial intelligence and biological inspiration.
Book Description
This book constitutes the proceedings of the 11th International Conference on Artificial General Intelligence, AGI 2018, held in Prague, Czech Republic, in August 2018. The 19 regular papers and 10 poster papers presented in this book were carefully reviewed and selected from 52 submissions. The conference encourage interdisciplinary research based on different understandings of intelligence, and exploring different approaches. As the AI field becomes increasingly commercialized and well accepted, maintaining and emphasizing a coherent focus on the AGI goals at the heart of the field remains more critical than ever.
Author: Peter Tse Publisher: Oxford University Press ISBN: 0198876971 Category : Psychology Languages : en Pages : 353
Book Description
This book offers an intellectually fierce defence of Libertarian Free Will seen from a neuroscientific and biological perspective. Tse argues that causation in living systems is dominated by non-linear goal-seeking automatic feedback loops and a continual criterial reparameterization of what will count as an adequate solution to goal fulfilment. For this reason, outcomes are neither determined nor random. That is, for each cycle, outcomes could have turned out differently than they actually did. Humans, he argues, have two kinds of libertarian free will. One type concerns the ability to choose freely and is shared with other highly developed animals. Second-order free will, in contrast, is uniquely human, and concerns envisioning a new self, then working toward the realization of that vision over a long period of time. As such, free will is understood to be centrally realized in acts of imagining and deliberation, whether free actions follow or not. A Neurophilosophy of Libertarian Free Will discusses these key philosophical issues considering the latest data and theories of neuroscience and will be of interest to academics, students, and anyone interested in the issue of Free Will.
Author: Alfred R. Mele Publisher: Oxford University Press, USA ISBN: 0199333955 Category : Philosophy Languages : en Pages : 353
Book Description
This cutting-edge volume showcases work supported by a four-year, 4.4 million dollar project on free will and science. In fourteen new articles and an introduction, contributors explore the subject of free will from the perspectives of neuroscience; social, cognitive, and developmental psychology; and philosophy (both traditional and experimental).
Author: Youna Vandaele Publisher: Springer Nature ISBN: 3031558898 Category : Behavior modification Languages : en Pages : 369
Book Description
Zusammenfassung: This book explores the multiple facets of habit from diverse and complementary theoretical frameworks. It provides a complete overview of the cognitive, computational, and neural processes underlying the formation of distinct forms of habit. The objective of the book is to cover (1) the multiple definitions of the habit construct and the relation between different habit-related concepts, (2) the underlying brain circuits of habits, and (3) the possible involvement of habits in psychiatric disorders such as alcohol and substance use disorder. This book will be of interest to all researchers in behavioral and computational neuroscience, psychology, and psychiatry who are interested in associative learning and decision making, under normal and pathological conditions
Author: Ying Tan Publisher: Springer ISBN: 3319204661 Category : Computers Languages : en Pages : 612
Book Description
This book and its companion volumes, LNCS volumes 9140, 9141 and 9142, constitute the proceedings of the 6th International Conference on Swarm Intelligence, ICSI 2015 held in conjunction with the Second BRICS Congress on Computational Intelligence, CCI 2015, held in Beijing, China in June 2015. The 161 revised full papers presented were carefully reviewed and selected from 294 submissions. The papers are organized in 28 cohesive sections covering all major topics of swarm intelligence and computational intelligence research and development, such as novel swarm-based optimization algorithms and applications; particle swarm opt8imization; ant colony optimization; artificial bee colony algorithms; evolutionary and genetic algorithms; differential evolution; brain storm optimization algorithm; biogeography based optimization; cuckoo search; hybrid methods; multi-objective optimization; multi-agent systems and swarm robotics; Neural networks and fuzzy methods; data mining approaches; information security; automation control; combinatorial optimization algorithms; scheduling and path planning; machine learning; blind sources separation; swarm interaction behavior; parameters and system optimization; neural networks; evolutionary and genetic algorithms; fuzzy systems; forecasting algorithms; classification; tracking analysis; simulation; image and texture analysis; dimension reduction; system optimization; segmentation and detection system; machine translation; virtual management and disaster analysis.
Author: Mark H. Lee Publisher: Frontiers Media SA ISBN: 2889660451 Category : Medical Languages : en Pages : 209
Book Description
This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.
Author: Roderic A. Grupen Publisher: MIT Press ISBN: 0262363291 Category : Computers Languages : en Pages : 403
Book Description
A comprehensive introduction to the mathematical foundations of movement and actuation that apply equally to animals and machines. This textbook offers a computational framework for the sensorimotor stage of development as applied to robotics. Much work in developmental robotics is based on ad hoc examples, without a full computational basis. This book's comprehensive and complete treatment fills the gap, drawing on the principal mechanisms of development in the first year of life to introduce what is essentially an operating system for developing robots. The goal is to apply principles of development to robot systems that not only achieve new levels of performance but also provide evidence for scientific theories of human development.
Author: Gianluca Baldassarre Publisher: Frontiers E-books ISBN: 2889193721 Category : Autonomous robots Languages : en Pages : 351
Book Description
The aim of this Research Topic for Frontiers in Psychology under the section of Cognitive Science and Frontiers in Neurorobotics is to present state-of-the-art research, whether theoretical, empirical, or computational investigations, on open-ended development driven by intrinsic motivations. The topic will address questions such as: How do motivations drive learning? How are complex skills built up from a foundation of simpler competencies? What are the neural and computational bases for intrinsically motivated learning? What is the contribution of intrinsic motivations to wider cognition? Autonomous development and lifelong open-ended learning are hallmarks of intelligence. Higher mammals, and especially humans, engage in activities that do not appear to directly serve the goals of survival, reproduction, or material advantage. Rather, a large part of their activity is intrinsically motivated - behavior driven by curiosity, play, interest in novel stimuli and surprising events, autonomous goal-setting, and the pleasure of acquiring new competencies. This allows the cumulative acquisition of knowledge and skills that can later be used to accomplish fitness-enhancing goals. Intrinsic motivations continue during adulthood, and in humans artistic creativity, scientific discovery, and subjective well-being owe much to them. The study of intrinsically motivated behavior has a long history in psychological and ethological research, which is now being reinvigorated by perspectives from neuroscience, artificial intelligence and computer science. For example, recent neuroscientific research is discovering how neuromodulators like dopamine and noradrenaline relate not only to extrinsic rewards but also to novel and surprising events, how brain areas such as the superior colliculus and the hippocampus are involved in the perception and processing of events, novel stimuli, and novel associations of stimuli, and how violations of predictions and expectations influence learning and motivation. Computational approaches are characterizing the space of possible reinforcement learning algorithms and their augmentation by intrinsic reinforcements of different kinds. Research in robotics and machine learning is yielding systems with increasing autonomy and capacity for self-improvement: artificial systems with motivations that are similar to those of real organisms and support prolonged autonomous learning. Computational research on intrinsic motivation is being complemented by, and closely interacting with, research that aims to build hierarchical architectures capable of acquiring, storing, and exploiting the knowledge and skills acquired through intrinsically motivated learning. Now is an important moment in the study of intrinsically motivated open-ended development, requiring contributions and integration across a large number of fields within the cognitive sciences. This Research Topic aims to contribute to this effort by welcoming papers carried out with ethological, psychological, neuroscientific and computational approaches, as well as research that cuts across disciplines and approaches.
Author: Gianluca Baldassarre
Author: Gianluca Baldassarre
Author: Alexei V. Samsonovich
Author: Matthew Iklé
Author: Peter Tse
Author: Alfred R. Mele
Author: Youna Vandaele
Author: Ying Tan
Author: Mark H. Lee
Author: Roderic A. Grupen
Author: Gianluca Baldassarre