Download or read book Intrinsically Motivated Open Ended Learning in Autonomous Robots written by Vieri Giuliano Santucci and published by Frontiers Media SA. This book was released on 2020-02-19 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Intrinsic motivations and open ended development in animals humans and robots written by Gianluca Baldassarre and published by Frontiers E-books. This book was released on 2015-02-10 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Intrinsically Motivated Learning in Natural and Artificial Systems written by Gianluca Baldassarre and published by Springer Science & Business Media. This book was released on 2013-03-29 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book AIxIA 2021 Advances in Artificial Intelligence written by Stefania Bandini and published by Springer Nature. This book was released on 2022-07-18 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book AIxIA 2023 Advances in Artificial Intelligence written by Roberto Basili and published by Springer Nature. This book was released on 2023-11-02 with total page 499 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Intrinsically Motivated Reinforcement Learning A Promising Framework for Developmental Robot Learning written by and published by . This book was released on 2005 with total page 7 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Bioinspired Systems for Translational Applications From Robotics to Social Engineering written by José Manuel Ferrández Vicente and published by Springer Nature. This book was released on with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Applications of Evolutionary Computation written by Stephen Smith and published by Springer Nature. This book was released on with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Cognitive Robotics written by Angelo Cangelosi and published by MIT Press. This book was released on 2022-05-17 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Deep Reinforcement Learning written by Aske Plaat and published by Springer Nature. This book was released on 2022-06-10 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book ECAI 2020 written by G. De Giacomo and published by IOS Press. This book was released on 2020-09-11 with total page 3122 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 24th European Conference on Artificial Intelligence (ECAI 2020), held in Santiago de Compostela, Spain, from 29 August to 8 September 2020. The conference was postponed from June, and much of it conducted online due to the COVID-19 restrictions. The conference is one of the principal occasions for researchers and practitioners of AI to meet and discuss the latest trends and challenges in all fields of AI and to demonstrate innovative applications and uses of advanced AI technology. The book also includes the proceedings of the 10th Conference on Prestigious Applications of Artificial Intelligence (PAIS 2020) held at the same time. A record number of more than 1,700 submissions was received for ECAI 2020, of which 1,443 were reviewed. Of these, 361 full-papers and 36 highlight papers were accepted (an acceptance rate of 25% for full-papers and 45% for highlight papers). The book is divided into three sections: ECAI full papers; ECAI highlight papers; and PAIS papers. The topics of these papers cover all aspects of AI, including Agent-based and Multi-agent Systems; Computational Intelligence; Constraints and Satisfiability; Games and Virtual Environments; Heuristic Search; Human Aspects in AI; Information Retrieval and Filtering; Knowledge Representation and Reasoning; Machine Learning; Multidisciplinary Topics and Applications; Natural Language Processing; Planning and Scheduling; Robotics; Safe, Explainable, and Trustworthy AI; Semantic Technologies; Uncertainty in AI; and Vision. The book will be of interest to all those whose work involves the use of AI technology.
Download or read book Creativity and Robotics written by Patricia Alves-Oliveira and published by Frontiers Media SA. This book was released on 2022-11-03 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Towards Vygotskian Autotelic Agents written by Cédric Colas and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Building autonomous machines that can explore large environments, discover interesting interactions and learn open-ended repertoires of skills is a long-standing goal in artificial intelligence. Inspired by the remarkable lifelong learning of humans, the field of developmental machine learning aims at studying the mechanisms enabling autonomous machines to self-organize their own developmental trajectories and grow their own repertoires of skills. This research makes steps towards that goal.Reinforcement learning methods (RL) train learning agents to control their environment by maximizing future rewards and, thus, seem adapted to our purpose. Although it achieved impressive results in the last decade--beating humans at video games, chess, go or controlling robotic agents--it falls short of solving our goal. Indeed, RL agents demonstrate low autonomy and open-endedness because they usually target a (small) set of pre-defined tasks characterized by hand-defined reward functions. In this research, we transfer, adapt and extend ideas from a developmental framework called intrinsically motivated goal exploration process (IMGEP) to the RL setting. The resulting framework builds on goal-conditioned RL techniques to design autotelic RL agents: agents that are intrinsically motivated to represent, generate, pursue and master their own goals as a way to grow repertoires of skills.The efficient acquisition of open-ended repertoires of skills further requires agents to creatively generate novel goals out of the domain of known effects (creative exploration), to readily generalize their understanding of known skills to similar ones (systematic generalization), and to compose known skills to form new ones (composition). Inspired by developmental psychology, we propose to use language as a cognitive tool to support such properties.We organize the manuscript around these two notions: goals and language. The first part focuses on goals. It covers foundational concepts and related work on intrinsic motivations, reinforcement learning and developmental robotics before introducing our framework, goal-conditioned intrinsically motivated goal exploration process (GC-IMGEP), the intersection of RL and IMGEPs. Building on this framework, we present three computational studies of the properties of autotelic agents. We first show that we can use autotelic exploration to solve external hard-exploration tasks (study 1: GEP-PG and 2: ME-ES). We then move on to reward-free environments and propose CURIOUS, an autotelic agent that targets a diversity of goals, transfers knowledge across skills and organizes its own learning trajectory by pursuing goals associated with high learning progress (study 3).The second part focuses on language. Inspired by the pioneering work of Vygotsky and others, we first discuss existing communicative and cognitive uses of language for goal-directed artificial agents. Language facilitates human-agent communications, abstraction, systematic generalization, long-horizon control, but also creativity and mental simulations. In two subsequent computational studies, we propose to implement these two last cognitive uses of language. IMAGINE uses language both to learn goal representations from social interactions (communicative use) and to imagine out-of-distribution goals used to drive its creative exploration and enhance systematic generalization (cognitive use). In our last study, LGB trains a language-conditioned world model to generate a diversity of possible futures conditioned on linguistic descriptions. This leads to behavioral diversity and strategy-switching behaviors.
Download or read book Cognitive Robotics written by Hooman Samani and published by CRC Press. This book was released on 2015-10-16 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: The kimono-clad android robot that recently made its debut as the new greeter at the entrance of Tokyo's Mitsukoshi department store is just one example of the rapid advancements being made in the field of robotics.Cognitive robotics is an approach to creating artificial intelligence in robots by enabling them to learn from and respond to real-worl
Download or read book Advances in Artificial Life written by Fernando Almeida e Costa and published by Springer. This book was released on 2007-09-04 with total page 1218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th European Conference on Artificial Life, ECAL 2007, held in Lisbon, Portugal. The 125 revised full papers cover morphogenesis and development, robotics and autonomous agents, evolutionary computation and theory, cellular automata, models of biological systems and their applications, ant colony and swarm systems, evolution of communication, simulation of social interactions, self-replication, artificial chemistry.
Download or read book Interdisciplinary Approaches to Robot Learning written by John Demiris and published by World Scientific. This book was released on 2000 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation Robots are being used in increasingly complicated and demanding tasks, often in environments that are complex or even hostile. Underwater, space and volcano exploration are just some of the activities that robots are taking part in, mainly because the environments that are being explored are dangerous for humans. Robots can also inhabit dynamic environments, for example to operate among humans, not just in factories, but also taking on more active roles. Recently, for instance, they have made their way into the home entertainment market. Given the variety of situations that robots will be placed in, learning becomes increasingly important. Robot learning is essentially about equipping robots with the capacity to improve their behaviour over time, based on their incoming experiences. The papers in this volume present a variety of techniques. Each paper provides a mini-introduction to a subfield of robot learning. Some also give a fine introduction to the field of robot learning as a whole. Thereis one unifying aspect to the work reported in the book, namely its interdisciplinary nature, especially in the combination of robotics, computer science and biology. This approach has two important benefits: first, the study of learning in biological systems can provide robot learning scientists and engineers with valuable insights into learning mechanisms of proven functionality and versatility; second, computational models of learning in biological systems, and their implementation in simulated agents and robots, can provide researchers of biological systems with a powerful platform for the development and testing of learning theories.
Download or read book Embodied Artificial Intelligence written by Fumiya Iida and published by Springer. This book was released on 2004-07-02 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: Originating from a Dagstuhl seminar, the collection of papers presented in this book constitutes on the one hand a representative state-of-the-art survey of embodied artificial intelligence, and on the other hand the papers identify the important research trends and directions in the field. Following an introductory overview, the 23 papers are organized into topical sections on - philosophical and conceptual issues - information, dynamics, and morphology - principles of embodiment for real-world applications - developmental approaches - artificial evolution and self-reconfiguration