Final Program

 All relevant information about the sessions of ISICS 2016 main conference and social events are listed in the program booklet.

Program at a glance

* ISICS 2016 will take place at the Auditorium Aula Magna at the Faculty of Engineering.

* The Gala dinner will take place at the Yucatecan Restaurant La Chaya Maya, located at street 55, No. 510, Centro, 97000, Merida, Yucatan. In case your registration does not include the Gala dinner and you would like to attend, please contact This email address is being protected from spambots. You need JavaScript enabled to view it. 

* The Archaeological site to visit on Friday, March 18th, will be Chichen Itzá, one of the Seven Wonders of the World. For information and reservation on this tour, please contact Dr. Jorge Rios-Martinez at This email address is being protected from spambots. You need JavaScript enabled to view it.

* The Guided visit of Merida is included in the registration fee. A turistic bus will be parked at the main entry of the Faculty of Engineering, next to the Auditorium Aula Magna. The tour will take one hour.

Keynote Speakers

Wednesday March 16th, 10:00 - 11:00 A.M.

Dr. Petar Kormushev

Title: Robot Learning of Motor Skills:  How to Train Your Robot?

Abstract: In the near future, most households will likely have a domestic robot. But how would you teach your robot new tasks? Endowing robots with human-like abilities to perform physical tasks in a smooth and natural way has been a dream of many researchers. Ideally, robots should be able to acquire new skills through natural interaction with humans. However, acquiring new motor skills is not simple and involves various forms of learning. Some tasks can be successfully transferred to a robot using only imitation strategies. Other tasks can be learned better by the robot alone using reinforcement learning. The key to an efficient learning process lies in the interaction between imitation and self-improvement strategies. This talk will overview the existing methods for robot learning of new motor skills. A variety of example tasks will be presented, such as: learning to manipulate objects, learning efficient bipedal locomotion, whole-body motor skill learning, learning to recover from failures, etc. Throughout these examples, the important role of the learning algorithm and the task representation will be highlighted. Finally, a glimpse of the cutting-edge research and open problems in this area will be given.

Wednesday March 16th, 2:00 - 3:00 P.M.

Dr. Carlos A. Coello Coello

Title: Evolutionary Multi-Objective Optimization: Current and Future Trends

Abstract: During the last few years, there has been an increasing interest in using heuristic search algorithms based on natural selection (the so-called "evolutionary algorithms") for solving a wide variety of problems. As in any other discipline, research on evolutionary algorithms has become more specialized over the years, giving rise to a number of sub-disciplines. This talk deals with one of the emerging sub-disciplines that has become very popular due to its wide applicability: evolutionary multi-objective optimization (EMOO). EMOO refers to the use of evolutionary algorithms (or even other biologically-inspired heuristics) to solve problems with two or more (often conflicting) objectives. Unlike traditional (single-objective) problems, multi-objective optimization problems normally have more than one possible solution. Thus, traditional evolutionary algorithms (e.g., genetic algorithms) need to be modified in order to deal with such problems. This talk will provide a general overview of this field, including its historical origins, its most significant developments, some of its most important application areas and its current and future challenges.

 Thursday March 17th, 10:00 - 11:00 A.M.

Dr. Angel Kuri-Morales

Title: Defeating Big Data - Tackling Real-World Problems in the World Banking Environment with Computational Intelligence

Abstract: For years classical closed mathematical techniques have been applied to modeling complex "real-world" problems. For example, in the commercial - particularly banking - environment the analysis, characterization and forecasting of large data bases (DBs) has occupied the experts over decades. Such techniques usually demand the DBs to comply with certain mathematical conditions which are typically not met. The usual methodology relies on replacing the actual data with approximations which do comply with the mathematical requirements. But machine learning, evolutionary computation, fuzzy logic and other computational techniques have been developed in an effort to achieve a new analytic paradigm. This new paradigm (herein referred to as "Computational Intelligence" (CI)) rests on the premise that data collected from the system (if adequately selected and processed) will yield enough information so as to characterize it without the need of previous expert knowledge. Some of the CI techniques were born as - sometimes colorful - analogies to biological, physical and/or social entities which seem to exhibit "intelligent" attributes. This successful motivational approach seems to suggest that the resulting methods (such as neural networks (NNs) or genetic algorithms (GAs), for example) are, somehow, näive oversimplifications which will, only sometimes, capture the complex mathematical relationships underlying real-world systems. But since their inception, both NNs and GAs have undergone a theoretical underpinning which allows them to be considered rugged mathematical tools. Under this light CI offers significant advantages over classical statistical methods. In this talk we will describe how CI has been applied to very large (over 12 million records) real world DBs to a) Determine the optimal sampling strategy, b) Reliably forecast the behavior of strategic variables c) Pinpoint the clusters of the DBs and d) Characterize the said clusters in terms of intuitive concepts. These strategy has been applied successfully and adopted as standard in at least one international bank conglomerate. We describe the methods and illustrate with practical applications.

Thursday March 17th, 2:00 - 3:00 P.M. 

Dr. Raúl Rojas

Title: Intelligent Mobility for Smart Cities

Abstract: In this talk I will first describe the main industrial transformations that we are witnessing in this century, specially regarding urbanism, energy production and transportation. I will concentrate in the challenges of new forms of mobility such as car-sharing and automated systems. I will show the work we have been doing in Berlin developing autonomous vehicles. Recently we covered a route of 2400Km in Mexico, driving autonomously. I will describe the main problems we encountered and I will also show some videos of the experiment.