I work as a Assistant Professor at the Computer Science Department (DCC, IIMAS), Universidad Nacional Autónoma de México (UNAM). The areas of research of my interest include: Developmental Artificial Intelligence, Computational Creativity, Artificial Life, and Pattern Recognition.
International Conference on Computational Creativity
14-18 september, 2021
MY LATEST RESEARCH
Dev E-R: A computational model of early cognitive development as a creative process.
This work describes a computational model named Dev E-R (Developmental Engagement-Reflection) that, inspired by Piaget’s theory, simulates the assimilation-accommodation adaptation process. It is implemented with a new extended version of the computational model of creativity known as Engagement-Reflection. That is, this model simulates adaptation as a creative activity. We introduce here the implementation of our model on an agent that is initialized with basic reflex conducts and that through the interaction with a 3D virtual world, it is able to build new behaviors autonomously. The new acquired skills, according to Piaget’s theory, are typically observed in children that have reached the second and third substages of the sensorimotor period.
The Past, present, and future of artificial life.
For millennia people have wondered what makes the living different from the non-living. Beginning in the mid-1980s, artificial life has studied living systems using a synthetic approach: build life in order to understand it better, be it by means of software, hardware, or wetware. This review provides a summary of the advances that led to the development of artificial life, its current research topics, and open problems and opportunities. We classify artificial life research into 14 themes: origins of life, autonomy, self-organization, adaptation (including evolution, development, and learning), ecology, artificial societies, behavior, computational biology, artificial chemistries, information, living technology, art, and philosophy. Being interdisciplinary, artificial life seems to be losing its boundaries and merging with other fields.
Symmetry detection in 3D chain coded discrete curves and trees.
Symmetry detection in 2D and 3D shapes has been a classical problem in computer vision, computational geometry, and pattern recognition. One of the reasons of this interest, is because symmetry is related to the balance and harmony, and in most cases it is considered like a beautiful proportion. In this work we present different methods to detect mirror and rotational symmetries in 2D and 3D open and closed curves, and in trees represented by means of the orthogonal direction change chain code. These methods detect both global and local symmetries. They can also detect the number and position of the axes of symmetry. They are simple, easy to implement and fast to execute.