Introducing neuromodulation in deep neural networks to learn adaptive behaviours.

ABSTRACT: Animals excel at adapting their intentions, attention, and actions to the environment, making them remarkably efficient at interacting with a rich, unpredictable and ever-changing external world, a property that intelligent machines currently lack. Such an adaptation property relies heavily on cellular neuromodulation, the biological mechanism that dynamically controls intrinsic properties of neurons and their response to external stimuli in a context-dependent manner. In this paper, we take inspiration from cellular neuromodulation to construct a new deep neural network architecture that is specifically designed to learn adaptive behaviours. The network adaptation capabilities are tested on navigation benchmarks in a meta-reinforcement learning context and compared with state-of-the-art a

SUBMITTER: Vecoven N 

PROVIDER: S-EPMC6984695 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature