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Anticipatory Behavior in Adaptive Learning Systems [[electronic resource] ] : From Psychological Theories to Artificial Cognitive Systems / / edited by Giovanni Pezzulo, Martin V. Butz, Olivier Sigaud, Gianluca Baldassarre
Anticipatory Behavior in Adaptive Learning Systems [[electronic resource] ] : From Psychological Theories to Artificial Cognitive Systems / / edited by Giovanni Pezzulo, Martin V. Butz, Olivier Sigaud, Gianluca Baldassarre
Edizione [1st ed. 2009.]
Pubbl/distr/stampa Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2009
Descrizione fisica 1 online resource (XI, 335 p.)
Disciplina 004n/a
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Robotics
Automation
Artificial intelligence
Computers
Algorithms
Application software
Computers and civilization
Robotics and Automation
Artificial Intelligence
Computation by Abstract Devices
Algorithm Analysis and Problem Complexity
Computer Appl. in Social and Behavioral Sciences
Computers and Society
Soggetto genere / forma Kongress.
München (2008)
ISBN 3-642-02565-X
Classificazione SS 4800
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto From Sensorimotor to Higher-Level Cognitive Processes: An Introduction to Anticipatory Behavior Systems -- Anticipation in Psychology: Focus on the Ideomotor View -- ABC: A Psychological Theory of Anticipative Behavioral Control -- Anticipative Control of Voluntary Action: Towards a Computational Model -- Theoretical and Review Contributions -- Driven by Compression Progress: A Simple Principle Explains Essential Aspects of Subjective Beauty, Novelty, Surprise, Interestingness, Attention, Curiosity, Creativity, Art, Science, Music, Jokes -- Steps to a Cyber-Physical Model of Networked Embodied Anticipatory Behavior -- Neural Pathways of Embodied Simulation -- Anticipation and Dynamical Systems -- The Autopoietic Nature of the “Inner World” -- The Cognitive Body: From Dynamic Modulation to Anticipation -- Computational Modelling of Psychological Processes in the Individual and Social Domains -- A Neurocomputational Model of Anticipation and Sustained Inattentional Blindness in Hierarchies -- Anticipation of Time Spans: New Data from the Foreperiod Paradigm and the Adaptation of a Computational Model -- Collision-Avoidance Characteristics of Grasping -- The Role of Anticipation on Cooperation and Coordination in Simulated Prisoner’s Dilemma Game Playing -- Behavioral and Cognitive Capabilities Based on Anticipation -- A Two-Level Model of Anticipation-Based Motor Learning for Whole Body Motion -- Space Perception through Visuokinesthetic Prediction -- Anticipatory Driving for a Robot-Car Based on Supervised Learning -- Computational Frameworks and Algorithms for Anticipation, and Their Evaluation -- Prediction Time in Anticipatory Systems -- Multiscale Anticipatory Behavior by Hierarchical Reinforcement Learning -- Anticipatory Learning Classifier Systems and Factored Reinforcement Learning.
Record Nr. UNISA-996465533203316
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2009
Materiale a stampa
Lo trovi qui: Univ. di Salerno
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Anticipatory behavior in adaptive learning systems : from psychological theories to artificial cognitive systems / / Giovanni Pezzulo, Martin V. Butz, Olivier Sigaud, Gianluca Baldassarre
Anticipatory behavior in adaptive learning systems : from psychological theories to artificial cognitive systems / / Giovanni Pezzulo, Martin V. Butz, Olivier Sigaud, Gianluca Baldassarre
Edizione [1st ed. 2009.]
Pubbl/distr/stampa Berlin ; ; Heidelberg, : Springer-Verlag, 2009
Descrizione fisica 1 online resource (XI, 335 p.)
Disciplina 004n/a
Altri autori (Persone) BaldassarreGianluca
PezzuloGiovanni
SigaudOlivier
Collana Lecture notes in computer science
Soggetto topico Artificial intelligence
Machine learning
ISBN 3-642-02565-X
Classificazione SS 4800
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto From Sensorimotor to Higher-Level Cognitive Processes: An Introduction to Anticipatory Behavior Systems -- Anticipation in Psychology: Focus on the Ideomotor View -- ABC: A Psychological Theory of Anticipative Behavioral Control -- Anticipative Control of Voluntary Action: Towards a Computational Model -- Theoretical and Review Contributions -- Driven by Compression Progress: A Simple Principle Explains Essential Aspects of Subjective Beauty, Novelty, Surprise, Interestingness, Attention, Curiosity, Creativity, Art, Science, Music, Jokes -- Steps to a Cyber-Physical Model of Networked Embodied Anticipatory Behavior -- Neural Pathways of Embodied Simulation -- Anticipation and Dynamical Systems -- The Autopoietic Nature of the “Inner World” -- The Cognitive Body: From Dynamic Modulation to Anticipation -- Computational Modelling of Psychological Processes in the Individual and Social Domains -- A Neurocomputational Model of Anticipation and Sustained Inattentional Blindness in Hierarchies -- Anticipation of Time Spans: New Data from the Foreperiod Paradigm and the Adaptation of a Computational Model -- Collision-Avoidance Characteristics of Grasping -- The Role of Anticipation on Cooperation and Coordination in Simulated Prisoner’s Dilemma Game Playing -- Behavioral and Cognitive Capabilities Based on Anticipation -- A Two-Level Model of Anticipation-Based Motor Learning for Whole Body Motion -- Space Perception through Visuokinesthetic Prediction -- Anticipatory Driving for a Robot-Car Based on Supervised Learning -- Computational Frameworks and Algorithms for Anticipation, and Their Evaluation -- Prediction Time in Anticipatory Systems -- Multiscale Anticipatory Behavior by Hierarchical Reinforcement Learning -- Anticipatory Learning Classifier Systems and Factored Reinforcement Learning.
Record Nr. UNINA-9910483244303321
Berlin ; ; Heidelberg, : Springer-Verlag, 2009
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Computational and robotic models of the hierarchical organization of behavior / / Gianluca Baldassarre, Marco Mirolli, editors
Computational and robotic models of the hierarchical organization of behavior / / Gianluca Baldassarre, Marco Mirolli, editors
Edizione [1st ed. 2013.]
Pubbl/distr/stampa Heidelberg [Germany] : , : Springer, , 2013
Descrizione fisica 1 online resource (vi, 358 pages) : illustrations (some color)
Disciplina 004
006.3
150.72
612.8
Collana Gale eBooks
Soggetto topico Computational learning theory
ISBN 3-642-39875-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Chap. 1 - Computational and Robotic Models of the Hierarchical Organization of Behavior: An Overview -- Chap. 2 - Behavioral Hierarchy: Exploration and Representation -- Chap. 3 - Self-organized Functional Hierarchy Through Multiple Timescales: Neurodynamical Accounts for Behavioral Compositionality -- Chap. 4 - Autonomous Representation Learning in a Developing Agent -- Chap. 5 - Hierarchies for Embodied Action Perception -- Chap. 6 - Learning and Coordinating Repertoires of Behaviors with Common Reward: Credit Assignment and Module Activation -- Chap. 7 - Modular, Multimodal Arm Control Models -- Chap. 8 - Generalization and Interference in Human Motor Control -- Chap. 9 - A Developmental Framework for Cumulative Learning Robots -- Chap. 10 - The Hierarchical Accumulation of Knowledge in the Distributed Adaptive Control Architecture -- Chap. 11 - The Hierarchical Organization of Cortical and Basal Ganglia Systems: A Computationally Informed Review and Integrated Hypothesis -- Chap. 12 - Divide and Conquer: Hierarchical Reinforcement Learning and Task Decomposition in Humans -- Chap. 13 - Neural Network Modelling of Hierarchical Motor Function in the Brain -- Chap. 14 - Restoring Purpose in Behavior.
Record Nr. UNINA-9910437571503321
Heidelberg [Germany] : , : Springer, , 2013
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Intrinsically motivated learning in natural and artificial systems / / edited by Gianluca Baldassarre, Marco Mirolli
Intrinsically motivated learning in natural and artificial systems / / edited by Gianluca Baldassarre, Marco Mirolli
Edizione [2nd ed.]
Pubbl/distr/stampa New York, : Springer, 2013
Descrizione fisica 1 online resource (454 p.)
Disciplina 629.892
Altri autori (Persone) BaldassarreGianluca
MirolliMarco
Soggetto topico Robots
Intrinsic motivation
ISBN 3-642-32375-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Chap. 1 - Intrinsically Motivated Learning Systems: An Overview -- Chap. 2 - Intrinsic Motivation and Reinforcement Learning -- Chap. 3 - Functions and Mechanisms of Intrinsic Motivations -- Chap. 4 - Exploration from Generalization Mediated by Multiple Controllers -- Chap. 5 - Maximizing Fun by Creating Data with Easily Reducible Subjective Complexity -- Chap. 6 - The Role of the Basal Ganglia in Discovering Novel Actions -- Chap. 7 - Action Discovery and Intrinsic Motivation: A Biologically Constrained Formalisation -- Chap 8 - Novelty Detection as an Intrinsic Motivation for Cumulative Learning Robots -- Chap. 9 - Novelty and Beyond: Towards Combined Motivation Models and Integrated Learning Architectures -- Chap. 10 - The Hippocampal-VTA Loop: The Role of Novelty and Motivation in Controlling the Entry of Information into Long-Term Memory -- Chap. 11 - Deciding Which Skill to Learn When: Temporal-Difference Competence-Based Intrinsic Motivation (TD-CB-IM) -- Chap. 12 - Intrinsically Motivated Affordance Discovery and Modeling -- Chap. 13 - Intrinsically Motivated Learning of Real-World Sensorimotor Skills with Developmental Constraints -- Chap. 14 - Investigating the Origins of Intrinsic Motivation in Human Infants -- Chap. 15 - A Novel Behavioural Task for Researching Intrinsic Motivations -- Chap. 16 - The “Mechatronic Board”: A Tool to Study Intrinsic Motivations in Humans, Monkeys, and Humanoid Robots -- Chap. 17 - The iCub Platform: A Tool for Studying Intrinsically Motivated Learning.
Record Nr. UNINA-9910437572403321
New York, : Springer, 2013
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Intrinsically Motivated Open-Ended Learning in Autonomous Robots
Intrinsically Motivated Open-Ended Learning in Autonomous Robots
Autore Giuliano Santucci Vieri
Pubbl/distr/stampa Frontiers Media SA, 2020
Descrizione fisica 1 electronic resource (286 p.)
Soggetto topico Science: general issues
Neurosciences
Soggetto non controllato intrinsic motivation
Open-ended learning
Robotics
developmental robotics
Curiosity driven learning
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557730903321
Giuliano Santucci Vieri  
Frontiers Media SA, 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
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