Professor John McCall's Outputs (3)

Adaptive dynamic control of quadrupedal robotic gaits with artificial reaction networks. (2012)
Presentation / Conference Contribution
GERRARD, C.E., MCCALL, J., COGHILL, G.M. and MACLEOD, C. 2012. Adaptive dynamic control of quadrupedal robotic gaits with artificial reaction networks. In Huang, T., Zeng, Z., Li, C. and Leung, C.S. (eds.) Proceedings of the 19th International conference on neural information processing (ICONIP 2012), 12-15 November 2012, Doha, Qatar. Lecture notes in computer science, 7663. Berlin: Springer [online], part I, pages 280-287. Available from: https://doi.org/10.1007/978-3-642-34475-6_34

The Artificial Reaction Network (ARN) is a bio-inspired connectionist paradigm based on the emerging field of Cellular Intelligence. It has properties in common with both AI and Systems Biology techniques including Artificial Neural Networks, Petri N... Read More about Adaptive dynamic control of quadrupedal robotic gaits with artificial reaction networks..

Temporal patterns in artificial reaction networks. (2012)
Presentation / Conference Contribution
GERRARD, C., MCCALL, J., COGHILL, G.M. and MACLEOD, C. 2012. Temporal patterns in artificial reaction networks. In Villa, A.E.P., Duch, W., Érdi, P., Masulli, F. and Palm, G. (eds.) Artificial neural networks and machine learning: proceedings of the 22nd International conference on artificial neural networks (ICANN 2012), 11-14 September 2012, Lausanne, Switzerland. Lecture notes in computer science, 7552. Berlin: Springer [online], part I, pages 1-8. Available from: https://doi.org/10.1007/978-3-642-33269-2_1

The Artificial Reaction Network (ARN) is a bio-inspired connectionist paradigm based on the emerging field of Cellular Intelligence. It has properties in common with both AI and Systems Biology techniques including Artificial Neural Networks, Petri N... Read More about Temporal patterns in artificial reaction networks..

Problem dependent metaheuristic performance in Bayesian network structure learning. (2012)
Thesis
WU, Y. 2012. Problem dependent metaheuristic performance in Bayesian network structure learning. Robert Gordon University, PhD thesis.

Bayesian network (BN) structure learning from data has been an active research area in the machine learning field in recent decades. Much of the research has considered BN structure learning as an optimization problem. However, the finding of optimal... Read More about Problem dependent metaheuristic performance in Bayesian network structure learning..