Data Set Used
Innovative control strategies are needed to cope with the increasing urban traffic chaos. In most cases, the currently used strategies are based on a central traffic-responsive control system which can be demanding to implement and maintain. Therefore, a functional and spatial decentralization is desired. For this purpose, distributed artificial… (More)
This paper shows how to use a decision-theoretic task scheduler in order to automatically generate efficient intention selection functions for BDI agent-oriented programming languages. We concentrate here on the particular extensions to a known BDI language called AgentSpeak(L) and its interpreter which were necessary so that the integration with a task… (More)
Complete algorithms have been proposed to solve problems modelled as distributed constraint optimization (DCOP). However, there are only few attempts to address real world scenarios using this formalism, mainly because of the complexity associated with those algorithms. In the present work we compare three complete algorithms for DCOP, aiming at studying… (More)
In modern societies the demand for mobility is increasing daily. Hence, one challenge to researchers dealing with traffic and transportation is to find efficient ways to model and predict traffic flow, even if the behaviour of people in traffic is not a trivial problem. Increasingly more people travel longer distances and choose more complex routes and… (More)
This paper presents an overview of ITSUMO, a microscopic traffic simulator based on cellular automata. The implementation uses agent technologies with a bottom-up philosophy in mind. We give an overview of the system and some details of its modules (data, simulation, driver and information/visualization).
Most clustering methods rely on central data structures and/or cannot cope with dynamically changing settings. Besides, these methods need some hints about the target clustering. However, issues related to the current use of Internet resources (distribution of data, privacy, etc.) require new ways of dealing with data clustering. In multiagent systems this… (More)
The discovery of gene regulatory networks is a major goal in the field of bioinformatics due to their relevance, for instance, in the development of new drugs and medical treatments. The idea underneath this task is to recover gene interactions in a global and simple way, identifying the most significant connections and thereby generating a model to depict… (More)