Intrinsically Motivated Open Ended Learning In Autonomous Robots
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Intrinsically Motivated Open Ended Learning In Autonomous Robots
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Author : Vieri Giuliano Santucci
language : en
Publisher: Frontiers Media SA
Release Date : 2020-02-19
Intrinsically Motivated Open Ended Learning In Autonomous Robots written by Vieri Giuliano Santucci and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-19 with categories.
Intrinsic Motivations And Open Ended Development In Animals Humans And Robots
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Author : Gianluca Baldassarre
language : en
Publisher: Frontiers E-books
Release Date : 2015-02-10
Intrinsic Motivations And Open Ended Development In Animals Humans And Robots written by Gianluca Baldassarre and has been published by Frontiers E-books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-10 with Autonomous robots categories.
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.
Intrinsically Motivated Learning In Natural And Artificial Systems
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Author : Gianluca Baldassarre
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-29
Intrinsically Motivated Learning In Natural And Artificial Systems written by Gianluca Baldassarre 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 2013-03-29 with Computers categories.
It has become clear to researchers in robotics and adaptive behaviour that current approaches are yielding systems with limited autonomy and capacity for self-improvement. To learn autonomously and in a cumulative fashion is one of the hallmarks of intelligence, and we know that higher mammals engage in exploratory activities that are not directed to pursue goals of immediate relevance for survival and reproduction but are instead driven by intrinsic motivations such as curiosity, interest in novel stimuli or surprising events, and interest in learning new behaviours. The adaptive value of such intrinsically motivated activities lies in the fact that they allow the cumulative acquisition of knowledge and skills that can be used later to accomplish fitness-enhancing goals. Intrinsic motivations continue during adulthood, and in humans they underlie lifelong learning, artistic creativity, and scientific discovery, while they are also the basis for processes that strongly affect human well-being, such as the sense of competence, self-determination, and self-esteem. This book has two aims: to present the state of the art in research on intrinsically motivated learning, and to identify the related scientific and technological open challenges and most promising research directions. The book introduces the concept of intrinsic motivation in artificial systems, reviews the relevant literature, offers insights from the neural and behavioural sciences, and presents novel tools for research. The book is organized into six parts: the chapters in Part I give general overviews on the concept of intrinsic motivations, their function, and possible mechanisms for implementing them; Parts II, III, and IV focus on three classes of intrinsic motivation mechanisms, those based on predictors, on novelty, and on competence; Part V discusses mechanisms that are complementary to intrinsic motivations; and Part VI introduces tools and experimental frameworks for investigating intrinsic motivations. The contributing authors are among the pioneers carrying out fundamental work on this topic, drawn from related disciplines such as artificial intelligence, robotics, artificial life, evolution, machine learning, developmental psychology, cognitive science, and neuroscience. The book will be of value to graduate students and academic researchers in these domains, and to engineers engaged with the design of autonomous, adaptive robots. The contributing authors are among the pioneers carrying out fundamental work on this topic, drawn from related disciplines such as artificial intelligence, robotics, artificial life, evolution, machine learning, developmental psychology, cognitive science, and neuroscience. The book will be of value to graduate students and academic researchers in these domains, and to engineers engaged with the design of autonomous, adaptive robots.
Aixia 2021 Advances In Artificial Intelligence
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Author : Stefania Bandini
language : en
Publisher: Springer Nature
Release Date : 2022-07-18
Aixia 2021 Advances In Artificial Intelligence written by Stefania Bandini and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-18 with Computers categories.
This book constitutes revised selected papers from the refereed proceedings of the 20th International Conference of the Italian Association for Artificial Intelligence, AIxIA 2021, which was held virtually in December 2021. The 36 full papers included in this book were carefully reviewed and selected from 58 submissions; the volume also contains 12 extended and revised workshop contributions. The papers were organized in topical sections as follows: Planning and strategies; constraints, argumentation, and logic programming; knowledge representation, reasoning, and learning; natural language processing; AI for content and social media analysis; signal processing: images, videos and speech; machine learning for argumentation, explanation, and exploration; machine learning and applications; and AI applications.
Aixia 2023 Advances In Artificial Intelligence
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Author : Roberto Basili
language : en
Publisher: Springer Nature
Release Date : 2023-11-02
Aixia 2023 Advances In Artificial Intelligence written by Roberto Basili and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-02 with Computers categories.
This book constitutes the refereed proceedings of the XXIInd International Conference on AIxIA 2023 – Advances in Artificial Intelligence, AIxIA 2023, held in Rome, Italy, during November 6–10, 2023. The 33 full papers included in this book were carefully reviewed and selected from 53 submissions. They were organized in topical sections as follows: Argumentation and Logic Programming, Natural Language Processing, Machine Learning, Hybrid AI and Applications of AI.
Applications Of Evolutionary Computation
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Author : Stephen Smith
language : en
Publisher: Springer Nature
Release Date :
Applications Of Evolutionary Computation written by Stephen Smith and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Cognitive Robotics
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Author : Angelo Cangelosi
language : en
Publisher: MIT Press
Release Date : 2022-05-17
Cognitive Robotics written by Angelo Cangelosi and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-17 with Technology & Engineering categories.
The current state of the art in cognitive robotics, covering the challenges of building AI-powered intelligent robots inspired by natural cognitive systems. A novel approach to building AI-powered intelligent robots takes inspiration from the way natural cognitive systems—in humans, animals, and biological systems—develop intelligence by exploiting the full power of interactions between body and brain, the physical and social environment in which they live, and phylogenetic, developmental, and learning dynamics. This volume reports on the current state of the art in cognitive robotics, offering the first comprehensive coverage of building robots inspired by natural cognitive systems. Contributors first provide a systematic definition of cognitive robotics and a history of developments in the field. They describe in detail five main approaches: developmental, neuro, evolutionary, swarm, and soft robotics. They go on to consider methodologies and concepts, treating topics that include commonly used cognitive robotics platforms and robot simulators, biomimetic skin as an example of a hardware-based approach, machine-learning methods, and cognitive architecture. Finally, they cover the behavioral and cognitive capabilities of a variety of models, experiments, and applications, looking at issues that range from intrinsic motivation and perception to robot consciousness. Cognitive Robotics is aimed at an interdisciplinary audience, balancing technical details and examples for the computational reader with theoretical and experimental findings for the empirical scientist.
Deep Reinforcement Learning
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Author : Aske Plaat
language : en
Publisher: Springer Nature
Release Date : 2022-06-10
Deep Reinforcement Learning written by Aske Plaat and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-10 with Computers categories.
Deep reinforcement learning has attracted considerable attention recently. Impressive results have been achieved in such diverse fields as autonomous driving, game playing, molecular recombination, and robotics. In all these fields, computer programs have taught themselves to understand problems that were previously considered to be very difficult. In the game of Go, the program AlphaGo has even learned to outmatch three of the world’s leading players.Deep reinforcement learning takes its inspiration from the fields of biology and psychology. Biology has inspired the creation of artificial neural networks and deep learning, while psychology studies how animals and humans learn, and how subjects’ desired behavior can be reinforced with positive and negative stimuli. When we see how reinforcement learning teaches a simulated robot to walk, we are reminded of how children learn, through playful exploration. Techniques that are inspired by biology and psychology work amazingly well in computers: animal behavior and the structure of the brain as new blueprints for science and engineering. In fact, computers truly seem to possess aspects of human behavior; as such, this field goes to the heart of the dream of artificial intelligence. These research advances have not gone unnoticed by educators. Many universities have begun offering courses on the subject of deep reinforcement learning. The aim of this book is to provide an overview of the field, at the proper level of detail for a graduate course in artificial intelligence. It covers the complete field, from the basic algorithms of Deep Q-learning, to advanced topics such as multi-agent reinforcement learning and meta learning.
Intrinsically Motivated Reinforcement Learning A Promising Framework For Developmental Robot Learning
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Author :
language : en
Publisher:
Release Date : 2005
Intrinsically Motivated Reinforcement Learning A Promising Framework For Developmental Robot Learning written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.
One of the primary challenges of developmental robotics is the question of how to learn and represent increasingly complex behavior in a self-motivated, open-ended way Barto, Singh, and Chentanez (Barto, Singh, & Chentanez 2004; Singh, Barto, & Chentanez 2004) have recently presented an algorithm for intrinsically motivated reinforcement learning that strives to achieve broad competence in an environment in a task-nonspecific manner by incorporating internal reward to build a hierarchical collection of skills. This paper suggests that with its emphasis on task-general, self-motivated, and hierarchical learning, intrinsically motivated reinforcement learning is an obvious choice for organizing behavior in developmental robotics. We present additional preliminary results from a gridworld abstraction of a robot environment and advocate a layered learning architecture for applying the algorithm on a physically embodied system.
Creativity And Robotics
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Author : Patricia Alves-Oliveira
language : en
Publisher: Frontiers Media SA
Release Date : 2022-11-03
Creativity And Robotics written by Patricia Alves-Oliveira and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-03 with Technology & Engineering categories.