Description: Ecosystem-based Generative Models are computational approaches that simulate interactions within an ecosystem, generating data that reflects the complexity and dynamics of biological, social, or technological systems. These models are based on the idea that elements within an ecosystem do not operate in isolation but are interconnected, and their interactions can influence the overall behavior of the system. Through algorithms and simulation techniques, these models allow for the exploration of how different variables and conditions can affect the evolution and functioning of various ecosystems. Key characteristics of these models include the ability to represent multiple agents, adaptation to changes in the environment, and the possibility of making predictions about the future behavior of these systems. Their relevance lies in their application across various disciplines, such as biology, ecology, economics, and artificial intelligence, where understanding and predicting complex phenomena is sought. In summary, Ecosystem-based Generative Models are powerful tools for analyzing and understanding complex systems, providing a comprehensive view of the interactions that shape them.
