Intrinsic motivations and open-ended development in animals, humans, and robots
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 to...
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| 格式: | Online |
| 語言: | 英语 |
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Frontiers Media SA
2021
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| 在線閱讀: | 17701 |
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| _version_ | 1869523219030999040 |
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| author | Tom Stafford Marco Mirolli Richard Michael Ryan Gianluca Baldassarre Andrew Barto Peter Redgrave |
| author_browse | Andrew Barto Gianluca Baldassarre Marco Mirolli Peter Redgrave Richard Michael Ryan Tom Stafford |
| author_facet | Tom Stafford Marco Mirolli Richard Michael Ryan Gianluca Baldassarre Andrew Barto Peter Redgrave |
| author_sort | Tom Stafford |
| collection | Directory of Open Access Books |
| 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. |
| format | Online |
| id | doab-20.500.12854ir-50581 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | Frontiers Media SA |
| publisherStr | Frontiers Media SA |
| record_format | ojs |
| spelling | doab-20.500.12854ir-505812024-04-05T17:30:47Z Intrinsic motivations and open-ended development in animals, humans, and robots Tom Stafford Marco Mirolli Richard Michael Ryan Gianluca Baldassarre Andrew Barto Peter Redgrave RC321-571 BF1-990 Q1-390 computational models intrinsic motivations autonomous robotics novelty and surprise review cumulative learning and development brain and behavior reinforcement learning thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences 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. 2021-02-11T16:35:30Z 2021-02-11T16:35:30Z 2015-11-19 16:29:12 2015 book 17701 16648714 9782889193721 https://directory.doabooks.org/handle/20.500.12854/50581 eng Frontiers Research Topics image/jpeg Attribution 4.0 International http://www.frontiersin.org/books/Intrinsic_motivations_and_open-ended_development_in_animals_humans_and_robots/430 http://journal.frontiersin.org/researchtopic/1797/intrinsic-motivations-and-open-ended-development-in-animals-humans-and-robots Frontiers Media SA 10.3389/978-2-88919-372-1 10.3389/978-2-88919-372-1 bf5ce210-e72e-4860-ba9b-c305640ff3ae 9782889193721 350 open access |
| spellingShingle | RC321-571 BF1-990 Q1-390 computational models intrinsic motivations autonomous robotics novelty and surprise review cumulative learning and development brain and behavior reinforcement learning thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences Tom Stafford Marco Mirolli Richard Michael Ryan Gianluca Baldassarre Andrew Barto Peter Redgrave Intrinsic motivations and open-ended development in animals, humans, and robots |
| title | Intrinsic motivations and open-ended development in animals, humans, and robots |
| title_full | Intrinsic motivations and open-ended development in animals, humans, and robots |
| title_fullStr | Intrinsic motivations and open-ended development in animals, humans, and robots |
| title_full_unstemmed | Intrinsic motivations and open-ended development in animals, humans, and robots |
| title_short | Intrinsic motivations and open-ended development in animals, humans, and robots |
| title_sort | intrinsic motivations and open ended development in animals humans and robots |
| topic | RC321-571 BF1-990 Q1-390 computational models intrinsic motivations autonomous robotics novelty and surprise review cumulative learning and development brain and behavior reinforcement learning thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences |
| topic_facet | RC321-571 BF1-990 Q1-390 computational models intrinsic motivations autonomous robotics novelty and surprise review cumulative learning and development brain and behavior reinforcement learning thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences |
| url | 17701 |
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