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Action selection is the task of doing the right thing at the right time. It requires the assessment of available alternatives, executing those most appropriate, and resolving conflicts among competing goals and possibilities. Using advanced computational modelling, this book explores cutting-edge research into action selection in nature from a wide range of disciplines, from neuroscience to behavioural ecology, and even political science. It delivers new insights into both detailed and systems-level attributes of natural intelligence and demonstrates advances in methodological practice. Contributions from leading researchers cover issues including whether biological action selection is optimal, neural substrates for action selection in the vertebrate brain, perceptual selection in decision making, and interactions between group and individual action selection. This first integrated review of action selection in nature contains a balance of review and original research material, consolidating current knowledge into a valuable reference for researchers while illustrating potential paths for future studies.
"Action selection is a fundamental problem in biology and ecology. It requires determining available alternatives, executing those most appropriate, and resolving conflicts among competing goals and possibilities. Using advanced computational modelling, this book explores cutting-edge research into action selection in nature from a wide range of disciplines, from neuroscience to behavioural ecology, and even political science. It delivers new insights into both detailed and systems-level attributes of natural intelligence and demonstrates advances in methodological practice. Contributions from leading researchers cover issues including whether biological action selection is optimal, neural substrates for action selection in the vertebrate brain, perceptual selection in decision making, and interactions between group and individual action selection. This first integrated review of action selection in nature contains a balance of review and original research material, consolidating current knowledge into a valuable reference for researchers, while illustrating potential paths for future studies"--
It's hard to conceive of a topic of more broad and personal interest than the study of the mind. In addition to its traditional investigation by the disciplines of psychology, psychiatry, and neuroscience, the mind has also been a focus of study in the fields of philosophy, economics, anthropology, linguistics, computer science, molecular biology, education, and literature. In all these approaches, there is an almost universal fascination with how the mind works and how it affects our lives and our behavior. Studies of the mind and brain have crossed many exciting thresholds in recent years, and the study of mind now represents a thoroughly cross-disciplinary effort. Researchers from a wide range of disciplines seek answers to such questions as: What is mind? How does it operate? What is consciousness? This encyclopedia brings together scholars from the entire range of mind-related academic disciplines from across the arts and humanities, social sciences, life sciences, and computer science and engineering to explore the multidimensional nature of the human mind.
This book constitutes the refereed proceedings of the 9th International Conference on Simulation of Adaptive Behavior, SAB 2006. The 35 revised full papers and 35 revised poster papers presented are organized in topical sections on the animat approach to adaptive behaviour, perception and motor control, action selection and behavioral sequences, navigation and internal world models, learning and adaptation, evolution, collective and social behaviours, applied adaptive behavior and more.
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.
The basal ganglia has received much attention over the last two decades, as it has been implicated in many neurological and psychiatric disorders. Most of this research—in both animals and humans—attempt to understand the neural and biochemical substrates of basic motor and learning processes, and how these are affected in human patients as well as animal models of brain disorders. The current volume contains research articles and reviews describing basic, pre-clinical and clinical neuroscience research of the basal ganglia written by attendees of the 11th Triennial Meeting of the International Basal Ganglia Society (IBAGS) that was held March 3-7th, 2013 at the Princess Hotel, Eilat, Israel and by researchers of the basal ganglia. Specifically, articles in this volume include research reports on the biochemistry, computational theory, anatomy and physiology of single neurons and functional circuitry of the basal ganglia networks as well as the latest data on animal models of basal ganglia dysfunction and clinical studies in human patients.
Today’s mobile robot perception is insu?cient for acting goal-directedly in - constrained, dynamic everyday environments like a home, a factory, or a city. Subject to restrictions in bandwidth, computer power, and computation time, a robot has to react to a wealth of dynamically changing stimuli in such - vironments, requiring rapid, selective attention to decisive, action-relevant - formation of high current utility. Robust and general engineering methods for e?ectively and e?ciently coupling perception, action, and reasoning are unava- able. Interesting performance, if any, is currently only achieved by sophisticated robot programming exploiting domain features and specialties, which leaves - dinary users no chance of changing how the robot acts. The latter facts are high barriers for introducing, for example, service robots into human living or work environments. In order to overcome these barriers, additonal R&D e?orts are required. The European Commission is undert- ing a determined e?ort to fund related basic, inter-disciplinary research in a line of Strategic Objectives, including the Cognitive Systems calls in their 6th Framework Programme (FP6, [1]), and continuing in the 7th Framework P- gramme.OneofthefundedCognitiveSystemsprojectsisMACS(“multi-sensory autonomous cognitive systems interacting with dynamic environments for p- ceiving and using a?ordances”).
Combining the study of animal minds, artificial minds, and human evolution, this book examine the advances made by comparative psychologists in explaining the intelligent behaviour of primates, the design of artificial autonomous systems and the cognitive products of language evolution.
Mastering the sensorimotor capabilities of our body is a skill that we acquire and refine over time, starting at the prenatal stages of development. This learning process is linked to brain development and is shaped by the rich set of multimodal information experienced while exploring and interacting with the environment. Evidence coming from neuroscience suggests the brain forms and mantains body representations as the main strategy to this mastering. Although it is still not clear how this knowledge is represented in our brain, it is reasonable to think that such internal models of the body undergo a continuous process of adaptation. They need to match growing corporal dimensions during development, as well as temporary changes in the characteristics of the body, such as the transient morphological alterations produced by the usage of tools. In the robotics community there is an increasing interest in reproducing similar mechanisms in artificial agents, mainly motivated by the aim of producing autonomous adaptive systems that can deal with complexity and uncertainty in human environments. Although promising results have been achieved in the context of sensorimotor learning and autonomous generation of body representations, it is still not clear how such low-level representations can be scaled up to more complex motor skills and how they can enable the development of cognitive capabilities. Recent findings from behavioural and brain studies suggests that processes of mental simulations of action-perception loops are likely to be executed in our brain and are dependent on internal motor representations. The capability to simulate sensorimotor experience might represent a key mechanism behind the implementation of further cognitive skills, such as self-detection, self-other distinction and imitation. Empirical investigation on the functioning of similar processes in the brain and on their implementation in artificial agents is fragmented. This e-book comprises a collection of manuscripts published by Frontiers in Robotics and Artificial Intelligence, under the section Humanoid Robotics, on the research topic re-enactment of sensorimotor experience for cognition in artificial agents. This compendium aims at condensing the latest theoretical, review and experimental studies that address new paradigms for learning and integrating multimodal sensorimotor information in artificial agents, re-use of the sensorimotor experience for cognitive development and further construction of more complex strategies and behaviours using these concepts. The authors would like to thank M.A. Dylan Andrade for his art work for the cover.