Exploring the Relationship Between Topology and Function in Evolved Neural Networks

Understanding the relationship between structure and function in neural networks is essential to explaining their operation. Greater awareness of the link between topology and application could lead to wider adoption, particularly in mission-critical systems. Here, we examine and analyze the topolog...

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Veröffentlicht in:	2020 IEEE Symposium Series on Computational Intelligence (SSCI) S. 2304 - 2311
Hauptverfasser:	Showalter, Ian, Schwartz, Howard
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.12.2020
Schlagworte:	Artificial Neural Network Autonomous Vehicle Biological neural networks Complexity theory Evolutionary computation Games Hebbian Learning Lamarckian Inheritance Multiobjective Network topology Neurocontrollers Neuroevolution Neuromodulation Pursuit-Evasion Topology Unsupervised Learning
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