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Internal Simulation of an Agent’s Intentions

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 196)

Abstract

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Lund University Cognitive Science, KungshusetLundSweden
  2. 2.Department of Chemical, Management, Computer, Mechanical EngineeringThe University of PalermoPalermoItaly

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