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Imitation: Learning and communication
2000This paper focuses on our works on imitation in autonomous robots. In a first part, we take into account recent studies in the field of developmental psychology and consider the two functions of imitation (learning and communication) that these studies have stressed.
Andry, Pierre +4 more
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Relational Learning by Imitation
2009Imitative learning can be considered an essential task of humans development. People use instructions and demonstrations provided by other human experts to acquire knowledge. In order to make an agent capable of learning through demonstrations, we propose a relational framework for learning by imitation. Demonstrations and domain specific knowledge are
Grazia Bombini +4 more
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Learning birdsong by imitation
Science, 2019Transforming sensory information into vocal imitation allows young finches to ...
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Machine learning by imitating human learning
Minds and Machines, 1996Learning general concepts in imperfect environments is difficult since training instances often include noisy data, inconclusive data, incomplete data, unknown attributes, unknown attribute values and other barriers to effective learning. It is well known that people can learn effectively in imperfect environments, and can manage to process very large ...
Kuo Chin Chang +2 more
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Robot learning—Beyond imitation
Science Robotics, 2019This special issue covers many aspects and applications of robot learning, including current progress, opportunities, and challenges.
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Learning nonparametric policies by imitation
2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2008A long cherished goal in artificial intelligence has been the ability to endow a robot with the capacity to learn and generalize skills from watching a human teacher. Such an ability to learn by imitation has remained hard to achieve due to a number of factors, including the problem of learning in high-dimensional spaces and the problem of uncertainty.
David B. Grimes, Rajesh P. N. Rao
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Imitation Learning in Uncertain Environments
2008This paper describes a new evolutionary learning method to handle the fast adaptation of a group of agents in an uncertain environment. The method is a result of our research towards the generation of intelligent agents in computer games and is inspired by the idea of social learning or cultural evolution.
Steffen Priesterjahn, Markus Eberling
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