no code implementations • 20 Jul 2018 • Sharat Chidambaran, Amir Behjat, Souma Chowdhury
Majority of Artificial Neural Network (ANN) implementations in autonomous systems use a fixed/user-prescribed network topology, leading to sub-optimal performance and low portability.
no code implementations • 17 Mar 2019 • Amir Behjat, Sharat Chidambaran, Souma Chowdhury
Neuroevolution is a process of training neural networks (NN) through an evolutionary algorithm, usually to serve as a state-to-action mapping model in control or reinforcement learning-type problems.
no code implementations • 31 May 2019 • Amir Behjat, Krushang Gabani, Souma Chowdhury
Neuroevolution, which uses evolutionary algorithms to simultaneously optimize the topology and weights of neural networks, is used as the learning method -- which operates over a set of sample approach scenarios.
no code implementations • 29 Jul 2020 • Amir Behjat, Manaswin Oddiraju, Mohammad Ali Attarzadeh, Mostafa Nouh, Souma Chowdhury
Further novel contribution occurs through the development of an inverse modeling approach that can instantaneously produce the 1D metamaterial design with minimum mass for a given desired non-resonant frequency range.