Emergence of Autonomous Behaviors of Virtual Characters through Simulated Reproduction

Abstract

This paper addresses the problem of autonomous behaviors of virtual characters. We postulate that a behavior is regarded as autonomous when the actions performed by the agent result from the interaction between its internal dynamics and the environment, rather than being externally controlled. In this work, we argue that an autonomous behavior is an agent's solution to a given problem, which is obtained through a process of self-organization of the dynamics of a system that is composed of the agent's controller, its body and the environment. That process allows the emergence of complex behaviors without any description of actions or objectives. We show a technique capable of adapting an artificial neural network to consistently control virtual Khepera-like robots by means of simulated reproduction, with no measure of the robots' fitness. All the robots are either male or female, and they are capable of evolving different kinds of behaviors according to their own characteristics, guided solely by the environment's dynamics.

Artificial Neural Network in Virtual Reality : A Survey

“…Its objective is to develop a neural network with growing topologies that can simultaneously give rise to multiple characteristics in an agent (Nogueira et al 2013b). It is also possible to enable reproduction in a simulated environment which increases the life span of an agent (Nogueira et al 2013a). A virtual ecosystem was created in which locomotion and food searching behavior is controlled using Recurrent Neural Network (RNN) (Ouannes et al 2012).…”

Emergent Navigation Behavior of Autonomous Virtual Agents Endowed with an Evolved Visual Cortex

“…Seeking virtual characters with more natural and realistic behaviors or greater compatibility between the characteristics of the characters and the environments they populate, Nogueira et al [1] [2] applied techniques inspired by the Embodied and Enactive Artificial Intelligence in order to generate emergent behaviors of virtual characters. The authors define an emergent behavior as one that is not explicitly described in any of the elements of the system, emerging as a result of the dynamic interactions of the components as well as its individual specific properties [1]. In [2], the authors describe a system based on a plastic neuromodulated network, capable of modulating itself to received stimuli, and a simple method for genetic encoding of the neural network controller.…”

“…Then, neurons are paired by their terminals to create the synapses arriving at or leaving the neurons. This process allows evolving the neural networks using a simple canonical genetic algorithm [2] or even simulated sexual reproduction [1].…”

“…4) The Simulation of Evolution: In [1], the authors demonstrated the capacity of the reported genetic encoding in the evolution of various behaviors in a population of robots by simulated sexual reproduction. The proposed controller's model and its encoding were efficient in generating interesting emergent behaviors such as foraging, crossing and obstacle avoidance, without any description of objectives for the characters.…”

“…Therefore, in this paper, we present a study of the movement dynamics for an agent in a variety of simulation environments. In order to achieve this, in the study of evacuations, we use the approach of behavior generation for autonomous virtual characters proposed in [1] and [2]. However, we present a new sensorial description in which we propose the evolution of an artificial visual cortex based on images captured by a virtual camera.…”