Orlando Avila-García

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In this paper we investigate the use of hormonal feedback as a mechanism to modulate a " motivation-based, " home-ostatic action selection mechanism (ASM) in a robot. We have framed our study in the context of a dynamic, multi-robot, competitive " two-resource " action selection problem. The introduction of competitors has important consequences for action(More)
The animat approach to artificial intelligence proposes biologically-inspired control mechanisms for autonomous robots. One of the related subproblems is action selection or " what to do next ". Many action selection architectures have been proposed. Motivation-based architectures implement a combination between internal and external stimuli to choose the(More)
The relationship between Software Product Lines (SPL) and Model-Driven Engineering (MDE) is not new in the literature. It mainly focuses on the use of Domain-Specific Languages to specify application families, rather than using the more classic feature models. However, more recent works propose another important synergy: the use of feature models to specify(More)
The problem of action selection for an autonomous creature implies resolving conflicts between competing behavioral alternatives. These conflicts can be resolved either via competition, following a " winner-take-all " approach, or via cooperation in a " voting-based " approach. In this paper we present two robotic architectures implementing these(More)
—Legacy systems are usually made of two kind of artifacts: source code and databases. Typically, the maintenance of those systems is carried out through re-engineering processes. Although both artifacts can be independently maintained, for a more effective re-engineering of the whole system both should be analyzed and evolved jointly. This is mainly due to(More)
Mapping features to models is a necessary step when developing software product lines of models. In such product lines, we need to relate objects from feature models (i.e. features) to objects from model templates. In this report we show an extension to the AMW framework to specify those relations through weaving models.
We compare the performance of autonomous agents with three different behavior selection architec-tures (Static-Threshold, Winner-Takes-All and Voting-Based) in terms of survival in a large and complex dynamic virtual environment. Experiment results indicate both advantages and disadvantages when applying each architecture in such environmental conditions,(More)