Creating herd behavior by virtual agents using neural networks
The paper focuses on simulating an artificial life in which neural networks (recurrent (RNN) and Long Short Term Memory (LSTM) networks) control prey and predator agents. The research goal was to check whether a simple genetic algorithm evolves the LSTM based controller that competes with the classi...
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| Vydáno v: | Procedia computer science Ročník 192; s. 437 - 446 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier B.V
2021
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| Témata: | |
| ISSN: | 1877-0509, 1877-0509 |
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| Abstract | The paper focuses on simulating an artificial life in which neural networks (recurrent (RNN) and Long Short Term Memory (LSTM) networks) control prey and predator agents. The research goal was to check whether a simple genetic algorithm evolves the LSTM based controller that competes with the classic RNN controller in the real world. We also examined the impact of audio communication within a given species on the survival of agents. Our experiments evidenced the LSTM network results were slightly worse than the RNN controller. We also showed that prey agents developed herd behavior in response to predator pressure. They learned to form herds that allowed them to resist predator attacks. It was also possible to observe the prey agent’s cooperation in searching for food when the plants formed clusters. |
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| AbstractList | The paper focuses on simulating an artificial life in which neural networks (recurrent (RNN) and Long Short Term Memory (LSTM) networks) control prey and predator agents. The research goal was to check whether a simple genetic algorithm evolves the LSTM based controller that competes with the classic RNN controller in the real world. We also examined the impact of audio communication within a given species on the survival of agents. Our experiments evidenced the LSTM network results were slightly worse than the RNN controller. We also showed that prey agents developed herd behavior in response to predator pressure. They learned to form herds that allowed them to resist predator attacks. It was also possible to observe the prey agent’s cooperation in searching for food when the plants formed clusters. |
| Author | Slimak, Adrian Markowska-Kaczmar, Urszula |
| Author_xml | – sequence: 1 givenname: Urszula surname: Markowska-Kaczmar fullname: Markowska-Kaczmar, Urszula email: urszula.markowska-kaczmar@pwr.edu.pl organization: Department of Computational Intelligence, Wroclaw University of Science and Technology, Wyb. Wyspianskiego 27, 50-370 Wroclaw, Poland – sequence: 2 givenname: Adrian surname: Slimak fullname: Slimak, Adrian organization: Department of Computational Intelligence, Wroclaw University of Science and Technology, Wyb. Wyspianskiego 27, 50-370 Wroclaw, Poland |
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| Cites_doi | 10.1109/TEVC.2010.2059031 10.1093/beheco/arm109 10.1162/ARTL_a_00206 10.1371/journal.pone.0235750 10.1177/105971239200100105 10.1098/rsif.2013.0305 10.1016/j.asoc.2020.106177 10.1145/37402.37406 10.1016/j.physd.2019.132306 10.1016/j.ecolmodel.2015.02.018 |
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| Keywords | 2010 MSC: : 92B20 62M45 68T05 Neural networks related approaches learning neural networks artificial life and related topics adaptive systems |
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| Title | Creating herd behavior by virtual agents using neural networks |
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