Neural Computing and Applications

, Volume 18, Issue 5, pp 431–446

AI-SIMCOG: a simulator for spiking neurons and multiple animats’ behaviours

ISNN 2008

DOI: 10.1007/s00521-009-0254-2

Cite this article as:
Cyr, A., Boukadoum, M. & Poirier, P. Neural Comput & Applic (2009) 18: 431. doi:10.1007/s00521-009-0254-2


Designing a biologically inspired neural architecture as a controller for a complete animat or physical robot environment, to test the hypotheses on intelligence or cognition is non-trivial, particularly, if the controller is a network of spiking neurons. As a result, simulators that integrate spike coding and artificial or real-world platforms are scarce. In this paper, we present artificial intelligence simulator of cognition, a software simulator designed to explore the computational power of pulsed coding at the level of small cognitive systems. Our focus is on convivial graphical user interface, real-time operation and multilevel Hebbian synaptic adaptation, accomplished through a set of non-linear dynamic weights and on-line, life-long modulation. Inclusions of transducer and hormone components, intrinsic oscillator and several learning functions in a discrete spiking neural algorithm are distinctive features of the software. Additional features are the easy link between the production of specific neural architectures and an artificial 2D-world simulator, where one or more animats implement an input–output transfer function in real-time, as do robots in the real world. As a result, the simulator code is exportable to a robot’s microprocessor. This realistic neural model is thus amenable to investigate several time related cognitive problems.


Simulator Artificial intelligence Spiking neurons model Learning and memory Dynamical synapse Robot 

Copyright information

© Springer-Verlag London Limited 2009

Authors and Affiliations

  1. 1.Computer Science DepartmentUniversité du Québec à MontréalMontrealCanada
  2. 2.Philosophy DepartmentUniversité du Québec à MontréalMontrealCanada

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