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.
2015 - Present
FET-OPEN H2020 project funded by the European Union that aims to produce swarm of sensor network agents to explore and monitor difficult-to-access environments.
10.2015 - 10.2019
The parameters of evolutionary algorithms (i.e. type of evolutionary operator and their parameters) influence the behavior of the search process. We investigate ways of optimizing the parameters of the algorithms to perform an efficient search.
Inspired by the evolutionary process, the research field known as Neuroevolution aims to optimize Artificial Neural Networks using evolutionary algorithms. We investigate efficient Neuroevolution approaches.
2012 - Present
Biologically Inspired AI