©2019 by Anil Yaman.

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©2019 by Anil Yaman.

Biologically Inspired Learning

2015 - Present

The plasticity property is one of the fundamental property of Biological Neural Networks which allows them to change their configuration over lifetime. In this project, we aim to produce plasticity property in Artificial Neural Networks to allow lifetime leaning inspired by the Biological Neural Networks.

Keywords:

continual learning, lifetime learning, plastic networks

Results

Introducing plasticity property in Artificial Neural Networks to perform local synaptic changes based on neuron activations and reinforcement signals received after every action of the networks.

Based on: 
Evolving Plasticity for Autonomous Learning under Changing Environmental Conditions.

arXiv preprint arXiv:1904.01709. 2019. 

Introducing local heuristics to perform synaptic changes in Artificial Neural Networks based on delayed reinforcement signals.

Based on:

Learning with Delayed Synaptic Plasticity. In Proceedings of the GECCO 2019.

Projects
Biologically Inspired Learning

Biologically Inspired Learning

2015 - Present

Neuroevolution

Neuroevolution

2012 - Present

Phoenix Project

Phoenix Project

10.2015 - 10.2019

Parameter Control in Evolutionary Algorithms

Parameter Control in Evolutionary Algorithms

2015 - Present