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Internal Simulation of an Agent`s Intentions

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Author

  • Magnus Johnsson
  • Miriam Buonamente

Editor

  • Antonio Chella

Summary, in English

We present the Associative Self-Organizing Map (A-SOM) and propose that it could be used to predict an agent's intentions by internally simulating the behaviour likely to follow initial movements. The A-SOM is a neural network that develops a representation of its input space without supervision, while simultaneously learning to associate its activity with an arbitrary number of additional (possibly delayed) inputs. We argue that the A-SOM would be suitable for the prediction of the likely continuation of the perceived behaviour of an agent by learning to associate activity patterns over time, and thus a way to read its intentions.

Department/s

Publishing year

2013

Language

English

Pages

175-176

Publication/Series

Biologically Inspired Cognitive Architectures 2012 (Advances in Intelligent Systems and Computing)

Volume

196

Document type

Conference paper

Publisher

Springer

Topic

  • Computer Vision and Robotics (Autonomous Systems)

Conference name

Biologically Inspired Cognitive Architectures 2012: Third Annual Meeting of the BICA Society

Conference date

2012-10-31 - 2012-11-03

Conference place

Palermo, Italy

Status

Published

Project

  • Thinking in Time: Cognition, Communication and Learning

ISBN/ISSN/Other

  • ISSN: 2194-5357
  • ISBN: 978-3-642-34274-5