Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
| Original language | English |
|---|---|
| Title of host publication | Artificial Neural Networks and Machine Learning – ICANN 2018 - 27th International Conference on Artificial Neural Networks, 2018, Proceedings |
| Publisher | Springer Verlag |
| Pages | 304-313 |
| Number of pages | 10 |
| ISBN (Print) | 9783030014179 |
| DOIs | |
| Publication status | E-pub ahead of print - 27 Sep 2018 |
| Event | 27th International Conference on Artificial Neural Networks, ICANN 2018 - Rhodes, Greece Duration: 4 Oct 2018 → 7 Oct 2018 |
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 11139 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
| Conference | 27th International Conference on Artificial Neural Networks, ICANN 2018 |
|---|---|
| Country/Territory | Greece |
| City | Rhodes |
| Period | 4/10/18 → 7/10/18 |
We evolved spiking neural network controllers for simple animats, allowing for these networks to change topologies and weights during evolution. The animats’ task was to discern one correct pattern (emitted from target objects) amongst other different wrong patterns (emitted from distractor objects), by navigating towards targets and avoiding distractors in a 2D world. Patterns were emitted with variable silences between signals of the same pattern in the attempt of creating a state memory. We analyse the network that is able to accomplish the task perfectly for patterns consisting of two signals, with 4 interneurons, maintaining its state (although not infinitely) thanks to the recurrent connections.
ID: 15580132