Seminar
- https://computing.phd.upc.edu/en/events/copy2_of_albcom-seminar
- Seminar
- 2012-11-09T00:00:00+01:00
- 2012-11-09T13:30:00+01:00
When
Nov 09, 2012 from 12:00 AM to 01:30 PM (Europe/Madrid / UTC100)
Where
Room S208 (floor -2), Omega Building, UPC, Barcelona
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Title: How Can Metaheuristics Help Software Engineers.
Speaker: Enrique Alba, Universidad de Málaga.
Time: 12:00 - 12:45
Abstract:
This presentation focuses on the potential benefits that metaheuristics (Genetic Algorithms, Ant Colonies, Particle Swarm, etc.) can bring to the field of Software Engineering (SE). For this to happen, we first need that a modelization of the SE problem is done in the form of an optimization, search or learning task. This is actually quite often the case in SE and other domains, thus allowing the utilization of powerful tools that can solve open problems in software testing, staff management for software projects, automatic tuning of communication protocols, model checking, next release problems, and a big amount of new challenges that can be now investigated thanks to the crossfertilization between these two domains. The talk will raise the main open questions in this new field as well as discuss on best practices, characterization, theory, and actual application of advanced search algorithms for software engineering.
Title: Boolean network robotics.
Speaker: Andrea Roli, Università di Bologna.
Time: 12:45 - 13:30
Abstract:
Dynamical systems theory and complexity science provide powerful tools for analysing artificial agents and robots. Furthermore, they have been recently proposed also as a source of design principles and guidelines. Boolean networks are a prominent example of complex dynamical systems and they have been shown to effectively capture important phenomena in gene regulation. From an engineering perspective, these models are very compelling, because they can exhibit rich and complex behaviours, in spite of the compactness of their description. Boolean network robotics concerns the use of Boolean networks, and other models from complex systems science, as robot programs. The network that controls the robot is designed by means of an automatic procedure based on stochastic local search techniques. In this talk, the main concepts of this recent research line will be presented and the latest results achieved will be illustrated.
Speaker: Enrique Alba, Universidad de Málaga.
Time: 12:00 - 12:45
Abstract:
This presentation focuses on the potential benefits that metaheuristics (Genetic Algorithms, Ant Colonies, Particle Swarm, etc.) can bring to the field of Software Engineering (SE). For this to happen, we first need that a modelization of the SE problem is done in the form of an optimization, search or learning task. This is actually quite often the case in SE and other domains, thus allowing the utilization of powerful tools that can solve open problems in software testing, staff management for software projects, automatic tuning of communication protocols, model checking, next release problems, and a big amount of new challenges that can be now investigated thanks to the crossfertilization between these two domains. The talk will raise the main open questions in this new field as well as discuss on best practices, characterization, theory, and actual application of advanced search algorithms for software engineering.
Title: Boolean network robotics.
Speaker: Andrea Roli, Università di Bologna.
Time: 12:45 - 13:30
Abstract:
Dynamical systems theory and complexity science provide powerful tools for analysing artificial agents and robots. Furthermore, they have been recently proposed also as a source of design principles and guidelines. Boolean networks are a prominent example of complex dynamical systems and they have been shown to effectively capture important phenomena in gene regulation. From an engineering perspective, these models are very compelling, because they can exhibit rich and complex behaviours, in spite of the compactness of their description. Boolean network robotics concerns the use of Boolean networks, and other models from complex systems science, as robot programs. The network that controls the robot is designed by means of an automatic procedure based on stochastic local search techniques. In this talk, the main concepts of this recent research line will be presented and the latest results achieved will be illustrated.
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