Cyr, A., Thériault, F. (2020). Same/different concept learning process: an embodied spiking neural implementation. (Soumis).
Cyr, A., Morand-Ferron, J., & Thériault, F. (2020). Dual exploration strategies using artificial spiking neural networks in a robotic learning task. Adaptive Behavior, 1059712320924744.
Cyr, A., Thériault, F., & Chartier, S. (2019). Revisiting the XOR problem: a neurorobotic implementation. Neural Computing and Applications, 1-9.DOI:10.1007/s00521-019-04522-0
Cyr, A., Thériault, F. (2019). Spatial concept learning: a spiking neural network implementation in virtual and physical robots. Special issue in Computational intelligence and neuroscience: Computational intelligence and neuroscience in Neurorobotics. DOI: 10.1155/2019/8361369
Cyr, A., Thériault, F., Ross, M., Berberian, N., & Chartier, S. (2018). Spiking neurons integrating visual stimuli orientation and direction selectivity in a robotic context. Frontiers in Neurorobotics, 12, 75.
Cyr, A., Thériault, F. (2018): Bio-inspired visual attention process using spiking neural networks controlling a camera. International Journal of Computational Vision and Robotics, 9(1). DOI: 10.1504/IJCVR.2019.098006
Cyr, A., Thériault, F., Ross, M., & Chartier, S. (2018, August). Associative Memory: A Spiking Neural Network Robotic Implementation. In International Conference on Artificial General Intelligence (pp. 32-41). Springer, Cham.
Cyr, A., Avarguès-Weber, A., & Thériault, F. (2017). Sameness/difference spiking neural circuit as a relational concept precursor model: A bio-inspired robotic implementation. Biologically Inspired Cognitive Architectures21, 59-66.
Ross, M., Berberian, N., Cyr, A., Thériault, F., & Chartier, S. (2017, September). Learning Distance-Behavioural Preferences Using a Single Sensor in a Spiking Neural Network. In International Conference on Artificial Neural Networks (pp. 110-118). Springer, Cham.
Cyr, André (2016). « Intelligence artificielle et robotique bio-inspirée : modélisation de fonctions d'apprentissage par réseaux de neurones à impulsions » Thèse. Montréal (Québec, Canada), Université du Québec à Montréal, Doctorat en informatique cognitive.
Cyr, A., & Thériault, F. (2015). Action selection and operant conditioning: a neurorobotic implementation. Journal of Robotics2015, 6.
Cyr, A., Boukadoum, M., & Thériault, F. (2014). Operant conditioning: a minimal components requirement in artificial spiking neurons designed for bio-inspired robot's controller. Frontiers in Neurorobotics8, 21.
Cyr, A., & Boukadoum, M. (2013). Habituation: a non-associative learning rule design for spiking neurons and an autonomous mobile robots implementation. Bioinspiration & biomimetics8(1), 016007.
Cyr, A., & Boukadoum, M. (2012). Classical conditioning in different temporal constraints: an STDP learning rule for robots controlled by spiking neural networks. Adaptive Behavior, 20.4 (2012): 257-272.
Cyr, A., Boukadoum, M., & Thériault, F. (2012). NeuroSim: A Virtual 3D-World to Investigate the Intelligence Phenomenon within the Perspective of Bio-inspired Robotic Agents. In "Virtual worlds: Artificial ecosystems and digital art exploration." Bornhofen, S., et al. eds., Science eBooks, Chapter 12, p. 167-185.