Imitation and Social Learning in Robots Humans and Animals Behavioural Social and Communicative Dimensions 1st Edition by Chrystopher Nehaniv, Kerstin Dautenhahn 0521845114 9780521845113

Imitation and Social Learning in Robots Humans and Animals Behavioural Social and Communicative Dimensions 1st Edition by Chrystopher Nehaniv, Kerstin Dautenhahn – Ebook PDF Instant Download/Delivery: 0521845114, 9780521845113

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ISBN 10: 0521845114

ISBN 13: 9780521845113

Author: Chrystopher L. Nehaniv, Kerstin Dautenhahn

Table of contents:

Part I: Correspondence problems and mechanisms
1 Imitation: thoughts about theories
1.1.1 Active Intermodal Mapping
1.1.2 Goal Directed Imitation
1.1.3 Associative Sequence Learning
1.2.1 Effector-dependent observational learning
1.2.2 Awareness and imitation
1.3 Intentional and incidental imitation
2.1 Matching behaviours
2.3 Granularity and metrics
2.4.1 What is matched
2.4.3 Learning
2.5.2 Stimulus/local enhancement
2.6.1 Rhythm, interaction and communicative kinesics
2.6.2 Relation to human–robot interaction
2.8 Learning what to imitate using measures of salience
3.1 Introduction
3.2 Challenges with using primitives
3.3 Research strategy
3.3.1 Testing environments
3.4 Learning from observation
3.5 Improving performance through practice
3.6 Discussion
Combining parameter selection and primitive execution
A. Selecting a primitive type and generating a sub-goal
B. Improving primitive selection and sub-goal generation from practice

Part II: Mirroring and ‘mind-reading’
4.1 Neurophysiology
4.2 Brain imaging
4.3 Computational properties
4.5 Ontogenesis
4.6 Empathy
4.7 A link to language
4.8 Process vs. representation
4.9 Conclusion
5.1.1 Simulation theory
5.1.2 Biological evidence
5.2.1 Fundamentals
5.2.2 Architectures
Design and Use of Inverse Models
5.3.1 Implementation of inverse models
5.3.3 Calculation of confidences
5.4 Experiments
5.5 Discussion
6.1 Introduction
6.2 Two models
6.2.2 Visual–visual matching
6.2.3 Mirror-correspondence understanding
6.2.4 Object-permanence understanding
Objectification
6.2.6 Kinesthetic–visual matching
Kinesthesis, vision and kinesthetic-visual matching in perception of one’s own body
Kinesthetic–visual matching between bodies (or body-images)
6.3 Motor imagery, kinesthetic–visual matching and the parietal region
The parietal region as the site for kinesthetic–visual matching
6.4 Imitation and other activities in early infancy as objections to the models
6.5 Summary

Part III: What to imitate?
7 The question of ‘what to imitate’: inferring goals and intentions from demonstrations
7.1.1 The functions of imitation
7.1.2 The components of a demonstration
7.1.3 Inferring goals
7.1.4 Implementing goals
7.1.5 Stepwise chain of events in imitation
7.2 How artificial systems currently answer the question of ‘what to imitate’
8.1 Introduction
8.2 Experimental set-up
8.3.1 Preprocessing by principal component analysis (PCA)
8.3.2 Encoding in hidden Markov models (HMMs)
8.3.5 Imitation metrics
Unidimensional case
Multidimensional case
8.4 Results and performance of the system
8.5 Discussion of the model
8.5.1 Similarity with work in psychology and ethology
Associative sequence learning (ASL)
Algebraic framework for the correspondence problem
9.1 Introduction
9.2 Towards imitation in populations
9.2.1 Agents
9.2.2 Imitation games
9.2.3 Embodiment
9.2.4 Self-organization
9.3 Imitation and communication
9.4.1 Monitoring performance
9.4.2 Results
9.5 Discussion

Part IV: Development and embodiment
10.1 Introduction
10.2 The imitative origins of mind-reading
10.4 Imitation and mind-reading in ASD
10.5 Imitation in autism
10.6 Neuroimaging of imitation in autism
10.7 Results
11.1 Introduction
11.2.1 Body babbling
11.2.2 Imitating body movements
11.2.3 Imitating actions on objects
11.2.4 Inferring intentions
11.3 A probabilistic model of imitation
11.3.1 Body babbling: learning internal models of one’s own body
11.3.2 Bayesian imitative learning
11.3.3 Example: learning to solve a maze task through imitation
11.3.3.1 Learning a forward model for the maze task
11.3.3.2 Imitation using the learned forward model and learned priors
11.3.3.3 Inferring the intent of the teacher
11.3.3.4 Summary
11.3.4 Further applications in robotic learning
11.3.5 Towards a probabilistic model for imitation in infants
11.4 Prospects for developmental robotics
12.1 The Agent-based perspective
12.2 ALICE overview
12.2.3 Building up the correspondence library
12.3 The CHESSWORLD testbed
12.3.1 Alice in Chessworld
12.4 The RABIT testbed
12.4.1 Metrics
Action metric
12.5 Experiments on aspects of imitation
12.5.1 Cultural transmission of behaviours and emergence of ‘proto-culture’
12.5.3 Proprioceptive matching
12.5.4 Loose perceptual matching
12.5.5 Changes in the agent embodiment
12.6 Conclusions and discussion

Part V: Synchrony and turn-taking as communicative mechanisms
13.1 Introduction
13.2.3 Kinesthesis
13.2.5 Autonomy
13.2.6 Attraction toward novelty
13.2.7 Perception–action coupling
13.3 Anything else needed to be an imitator?
13.4.1 The two adaptive functions of imitation: learning and communication
13.4.1.1 Turn-taking
13.4.1.2 Synchrony
13.4.2 Robot
13.4.2.1 Synchrony
13.5 Concluding comments
14.1 Intersubjectivity and turn-taking
14.2.2 Agent’s description
14.2.3 Evolution schema
14.3 Simulation results
14.3.2 Prediction breakdown
14.3.3 Coupling with a noise and a non-responding agent
14.3.4 Evolution of adaptability
14.4 Discussion

15.1.1 Overview
15.1.3 ‘Pure’ bully characteristics: mindreading and empathy
15.1.4 Precursors of bullying
15.1.4.1 How do bullies become bullies?
15.2.1 Imitation and inter-subjectivity
15.3.1 Deficits in empathy and autism
15.3.1.2 Empathy and psychopathy
15.3.1.4 Differences in empathy for autism and psychopathy
15.3.2 Empathy and bullying behaviour
15.3.2.1 The distinction between automatic and controlled empathy in bullies
15.4.1.1 Empathy as a tool for bullying intervention programmes
15.4.1.2 The use of imitative interactive behaviour for bullying interventions

Part VI: Why imitate? – Motivations
16 Multiple motivations for imitation in infancy
16.1 Neonatal imitation
16.2 Deferred imitation
16.3 Synchronic imitation
16.4 Imitation of intended but incomplete acts
16.5 Imitation from television
16.6 Changing motivations to imitate in development
16.7 Echolalia
16.8 The multi-faceted nature of imitation
17.1 Introduction
17.2 Progress-driven learning
17.2.2 Mastery-driven systems
17.2.3 Novelty-driven systems
17.2.4 The ‘screen’ problem
17.2.5 Progress-driven systems
17.2.6 Experimental results for the ‘screen problem’
17.3 Possible underlying developmental mechanisms for early imitation
17.3.2 Self-imitation (1–2 m)
17.3.3 Pseudo-imitation (2–4 m)
17.4 Conclusion

Part VII: Social feedback
18.1 Introduction
18.2 Animals, learning and cognitive processing
18.2.1 Studies on Grey parrots
18.2.2 The model/rival (M/R) technique
18.2.3 How aspects of M/R training affect learning
18.3.1 Current intervention strategies for children
18.3.2 What mediates M/R success?
19.1 Introduction
19.2 Action-based representations
19.3 Communication by acting – a means for robot–human interaction
19.3.1 Experiments in communication by acting
19.3.2 Discussion
19.4 Learning from imitation and additional cues
Generalization from a small number of examples
Learning from practice and teacher feedback
19.5 Related work
19.6 Conclusions

Part VIII: The ecological context
20 Emulation learning: the integration of technical and social cognition
20.1 Distinguishing between imitation and emulation
20.2 Studying an unusual species: the kea
20.3 The artificial fruit experiment
20.4 Technical intelligence in keas
20.5 Conclusion
21.1 Introduction
21.2 Forms of deceptive resemblance in nature
21.3 Fixed vs. dynamic mimicry
21.4 The cephalopods
21.5 Mimicry in cephalopods
21.6 Origins of dynamic mimicry

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Tags: Chrystopher Nehaniv, Kerstin Dautenhahn, Imitation, Social