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SpikingLab: modelling agents controlled by Spiking Neural Networks in Netlogo
- Source :
- Neural Computing & Applications
- Publication Year :
- 2016
- Publisher :
- Springer Science and Business Media LLC, 2016.
-
Abstract
- The scientific interest attracted by Spiking Neural Networks (SNN) has lead to the development of tools for the simulation and study of neuronal dynamics ranging from phenomenological models to the more sophisticated and biologically accurate Hodgkin-and-Huxley-based and multi-compartmental models. However, despite the multiple features offered by neural modelling tools, their integration with environments for the simulation of robots and agents can be challenging and time consuming. The implementation of artificial neural circuits to control robots generally involves the following tasks: (1) understanding the simulation tools, (2) creating the neural circuit in the neural simulator, (3) linking the simulated neural circuit with the environment of the agent and (4) programming the appropriate interface in the robot or agent to use the neural controller. The accomplishment of the above-mentioned tasks can be challenging, especially for undergraduate students or novice researchers. This paper presents an alternative tool which facilitates the simulation of simple SNN circuits using the multi-agent simulation and the programming environment Netlogo (educational software that simplifies the study and experimentation of complex systems). The engine proposed and implemented in Netlogo for the simulation of a functional model of SNN is a simplification of integrate and fire (I&F) models. The characteristics of the engine (including neuronal dynamics, STDP learning and synaptic delay) are demonstrated through the implementation of an agent representing an artificial insect controlled by a simple neural circuit. The setup of the experiment and its outcomes are described in this work.
- Subjects :
- Simulations
0301 basic medicine
Physical neural network
Neuro engineering
Computer science
Interface (Java)
NetLogo
Machine learning
computer.software_genre
Modelling
STDP
03 medical and health sciences
0302 clinical medicine
Neural circuit
Artificial Intelligence
Artificial life
Biological neural network
Membrane potential
computer.programming_language
Spiking neural network
Artificial neural network
business.industry
Agents
Neural engineering
Spiking neurons
Dependent plasticity
030104 developmental biology
Spike timing
Robot
Original Article
Artificial intelligence
business
Robots
computer
Neural networks
030217 neurology & neurosurgery
Software
Subjects
Details
- ISSN :
- 14333058 and 09410643
- Volume :
- 28
- Database :
- OpenAIRE
- Journal :
- Neural Computing and Applications
- Accession number :
- edsair.doi.dedup.....7afdd383c2e7c351b846cfb0ad9cd2ba
- Full Text :
- https://doi.org/10.1007/s00521-016-2398-1