Subsistema de locomoción de módulos funcionales en crecimiento

The Growing Functional Modules (GFM) approach allows the graphic generation of learning-based controllers. A controller is created by interconnecting and configuring four kinds of components: Global Goals, Acting Modules, Sensing Modules, and Sensations. The Sensations list describes the control loop feedback, the set of Global Goals specifies the intrinsic motivations of the controller, and the Acting and Sensing Modules dynamically develop their respective functionalities while interacting with the environment. In order to position GFM as a potential paradigm, this paper describes the development of a learning-based locomotion subsystem. This subsystem is consists of two new Acting Modules in charge of gross and fine motor skills, respectively. The implementation of these new modules is described and their functionality illustrated: The first is dedicated to mapping the environment and the second one to obstacle avoidance.El enfoque del módulo de crecimiento funcional (GFM, por sus siglas en inglés) permite la generación gráfica de controladores basados en aprendizaje. Un controlador se crea interconectando y configurando cuatro tipos de componentes: objetivos globales, módulos de actuación, módulos de detección y sensaciones. La lista de sensaciones describe la retroalimentación del bucle de control, el conjunto de objetivos globales especifica las motivaciones intrínsecas del controlador y los módulos de actuación y detección desarrollan dinámicamente sus respectivas funcionalidades mientras interactúan con el entorno. Con el fin de posicionar a GFM como un paradigma potencial, este artículo describe el desarrollo de un subsistema de locomoción basado en el aprendizaje, este subsistema está compuesto por dos Módulos Actuales a cargo de la motricidad gruesa y fina, respectivamente. Se describe la implementación de estos nuevos módulos y se ilustra su funcionalidad: el primero está dedicado a mapear el entorno y el segundo a evitar obstáculos

A growing functional module designed to trigger causal inference

"Growing Functional Modules" constitutes a prospective paradigm founded on the epigenetic approach whose proposal consists in designing a distributed architecture, based on interconnected modules, that allows the automatic generation of an autonomous and adaptive controller (artificial brain). The present paper introduces a new module designed to trigger causal inference; its functionality is discussed and its behavior is illustrated applying the module to solve the problem of a dynamic maze

A growing functional module designed to trigger causal inference

"Growing Functional Modules" constitutes a prospective paradigm founded on the epigenetic approach whose proposal consists in designing a distributed architecture, based on interconnected modules, that allows the automatic generation of an autonomous and adaptive controller (artificial brain). The present paper introduces a new module designed to trigger causal inference; its functionality is discussed and its behavior is illustrated applying the module to solve the problem of a dynamic maze