The what, how, and why of naturalistic behavior

In the past few years, advances in machine learning have fueled an explosive growth of descriptive and generative models of animal behavior. These new approaches offer higher levels of detail and granularity than has previously been possible, allowing for fine-grained segmentation of animals??? actions and precise quantitative mappings between an animal???s sensory environment and its behavior. How can these new methods help us understand the governing principles shaping complex and naturalistic behavior? In this review, we will recap ways in which our ability to detect and model behavior have improved in recent years, and consider how these techniques might be used to revisit classical normative theories of behavioral control.

Automated summary

Advances in machine learning have led to the growth of descriptive and generative models of animal behavior, offering higher levels of detail and granularity. These methods help us understand the governing principles behind complex and naturalistic behavior.