Ecosystem Models Based on Artificial Intelligence
Paper i proceeding, 2022
Ecosystem models can be used for understanding general phenomena of evolution, ecology, and ethology. They can also be used for analyzing and predicting the ecological consequences of human activities on specific ecosystems, e.g., the effects of agriculture, forestry, construction, hunting, and fishing. We argue that powerful ecosystem models need to include reasonable models of the physical environment and of animal behavior. We also argue that several well-known ecosystem models are unsatisfactory in this regard. Then we present the open-source ecosystem simulator Ecotwin, which is built on top of the game engine Unity. To model a specific ecosystem in Ecotwin, we first generate a 3D Unity model of the physical environment, based on topographic or bathymetric data. Then we insert digital 3D models of the organisms of interest into the environment model. Each organism is equipped with a genome and capable of sexual or asexual reproduction. An organism dies if it runs out of some vital resource or reaches its maximum age. The animal models are equipped with behavioral models that include sensors, actions, reward signals, and mechanisms of learning and decision-making. Finally, we illustrate how Ecotwin works by building and running one terrestrial and one marine ecosystem model.
Författare
Claes Strannegård
Göteborgs universitet
Chalmers, Data- och informationsteknik, Data Science och AI
Karolinska Institutet
Niklas Engsner
Karolinska Institutet
Chalmers, Data- och informationsteknik, Data Science
Jesper Eisfeldt
Karolinska Institutet
John Endler
Deakin University
Amanda Hansson
Göteborgs universitet
Rasmus Lindgren
Student vid Chalmers
Petter Mostad
Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik
Göteborgs universitet
Simon Olsson
Chalmers, Data- och informationsteknik, Data Science och AI
Irene Perini
Linköpings universitet
Center for Medical Image Science and Visualization
Heather Reese
Göteborgs universitet
Fulya Taylan
Karolinska Institutet
Simon Ulfsbäcker
Göteborgs universitet
Ann Nordgren
Karolinska Institutet
Göteborgs universitet
34th Workshop of the Swedish Artificial Intelligence Society, SAIS 2022
9781665471268 (ISBN)
34th Workshop of the Swedish Artificial Intelligence Society, SAIS 2022
Stockholm, Sweden,
Stockholm, Sweden,
Ämneskategorier
Bioinformatik (beräkningsbiologi)
Systemvetenskap
Datavetenskap (datalogi)
DOI
10.1109/SAIS55783.2022.9833026