Emergent behaviour and neural dynamics in artificial agents tracking odour plumes.

ABSTRACT: Tracking an odour plume to locate its source under variable wind and plume statistics is a complex task. Flying insects routinely accomplish such tracking, often over long distances, in pursuit of food or mates. Several aspects of this remarkable behaviour and its underlying neural circuitry have been studied experimentally. Here we take a complementary in silico approach to develop an integrated understanding of their behaviour and neural computations. Specifically, we train artificial recurrent neural network agents using deep reinforcement learning to locate the source of simulated odour plumes that mimic features of plumes in a turbulent flow. Interestingly, the agents' emergent behaviours resemble those of flying insects, and the recurrent neural networks learn to compute task-relevan

SUBMITTER: Singh SH 

PROVIDER: S-EPMC10601839 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature