Evolving Plastic Neuromodulated Networks for Behavior Emergence of Autonomous Virtual Characters

By Yuri Lenon Barbosa Nogueira, Carlos Brito, Creto Augusto Vidal, Joaquim Bento Cavalcante Neto. 2013

8 citations recorded by the source corpus.

This paper addresses the problem of generating natural behavior of autonomous virtual characters. Inspired by the fields of Embodied and Enactive Artificial Intelligence, we postulate that natural behavior is the result of a coupling between the agent and the world where it lives, which leads to a coherence between its actions and its surroundings. In this work, we present the tools that we have been using to study that idea: a controller based on a plastic neuromodulated neural network, which is capable of molding itself to received stimuli; and a simple novel method for genetic encoding of artificial neural networks. We show the capabilities of the controller in generating interesting foraging behavior of an autonomous virtual robot, and discuss the advantages of its emergent characteristics when compared with traditional approaches.

Subfields: Artificial Intelligence, Control and Systems Engineering

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Control and Systems Engineering

Citations in the corpus

Born to Learn: the Inspiration, Progress, and Future of Evolved Plastic Artificial Neural Networks (2017, background): “Nogueira et al. (2013) also reported evolutionary advantages in foraging behavior of an autonomous virtual robot when equipped with neuromodulated plasticity.”
Emergent vision system of autonomous virtual characters (2016, background): “In [24], we presented a controller for generating behaviors of virtual characters based on emergence.”