Distributed Representations, Simple Recurrent Networks, And Grammatical Structure
Machine Learning - Connectionist approaches to language learning
Cultural evolution in neural networks
IEEE Expert: Intelligent Systems and Their Applications
The agent-based perspective on imitation
Imitation in animals and artifacts
Imitation or something simpler? modeling simple mechanisms for social information processing
Imitation in animals and artifacts
Social learning mechanisms compared in a simple environment
ICAL 2003 Proceedings of the eighth international conference on Artificial life
Efficient Exploration In Reinforcement Learning
Efficient Exploration In Reinforcement Learning
Artificial neural network for sequence learning
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
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Imitation learning is a promising route to instruct robotic multi-agent systems. However, imitating agents should be able to decide autonomously what behavior, observed in others, is interesting to copy. Here we investigate whether a simple recurrent network (Elman Net) can be used to extract meaningful chunks from a continuous sequence of observed actions. Results suggest that, even in spite of the high level of task specific noise, Elman nets can be used for isolating re-occurring action patterns in robots. Limitations and future directions are discussed.