Cargando…
Co-Evolution of Predator-Prey Ecosystems by Reinforcement Learning Agents
The problem of finding adequate population models in ecology is important for understanding essential aspects of their dynamic nature. Since analyzing and accurately predicting the intelligent adaptation of multiple species is difficult due to their complex interactions, the study of population dyna...
Autores principales: | Park, Jeongho, Lee, Juwon, Kim, Taehwan, Ahn, Inkyung, Park, Jooyoung |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8069842/ https://www.ncbi.nlm.nih.gov/pubmed/33924723 http://dx.doi.org/10.3390/e23040461 |
Ejemplares similares
-
Predicting Human Motion Signals Using Modern Deep Learning Techniques and Smartphone Sensors
por: Kim, Taehwan, et al.
Publicado: (2021) -
Smartphone Sensor-Based Human Motion Characterization with Neural Stochastic Differential Equations and Transformer Model
por: Lee, Juwon, et al.
Publicado: (2022) -
Deep-Reinforcement Learning-Based Co-Evolution in a Predator–Prey System
por: Wang, Xueting, et al.
Publicado: (2019) -
A synthetic Escherichia coli predator–prey ecosystem
por: Balagaddé, Frederick K, et al.
Publicado: (2008) -
Prey density affects predator foraging strategy in an Antarctic ecosystem
por: Busdieker, Karl M., et al.
Publicado: (2019)