An Agent-Based Platform for Traffic Simulation
In this article is presented an agent-based platform to produce road traffic simulations. This is designed by the IDK tool of INGENIAS, allowing the specification of interactions between individuals, and among them and the nearby environment. It adopts development methodologies such as agent-based or model-driven, allowing greater flexibility achieving experimental designs. The obtained prototype is validated through a case study, which reproduces real situations coming from specificic observations made in road traffic.
Using Multi-Agent Systems to Facilitate the Acquisition of Workgroup Competencies
This paper presents a software architecture specifically designed to support the development of student teams. In order to do that Adaptive Multi-Agent Systems (AMAS) are used. Knowledge is specified declaratively by the UML-AT language (an extension of UML stereotypes and concepts adapted to the Activity Theory) and social properties. This allows an iterative definition and incremental of the events and workflows to consider.
A Model-Driven Engineering Process for Agent-Based Traffic Simulations
This article presents a complete process for road traffic simulations using Model-Driven Development. To do this two main phases are proposed: the first focused on traffic experts and a second based on simulation designers. The first uses a specific Modelling Language and the Eclipse modeling tools. The second is related to agent-based methodologies for platform-based designs. The result provides support for achieving the transition consisting of transforming existing traffic theories to simulations.
Best Paper Award
Developing an integrative modelling language for enhancing road traffic simulations
This article illustrates a case study which adopts a infrastructure based on Model Driven Development. This allows representing specific aspects of road traffic provided by theories of the domain and using an existing traffic simulation platforms as MATSim. The new simulation generated enhances the target platform introducing behavioural theories and decisions of individuals involved in traffic. Thus the viability of the artefacts provided by the infrastructure is shown.
An Integrative Framework for the Model-Driven Development of Traffic Simulations
In this article is introduced a development process that guides users in the implementation of road traffic simulations based on existing theories domain. It uses the development framework carried out during my research. The lifecycle of this process is represented by SPEM. A case study validates the proposal generating a road traffic simulation from a particular theory of the domain.
Model-Driven Engineering of Simulations for Smart Roads
In this publication is developed a Modeling Language capable of performing designs related to the simulation of smart roads. This has been built on the basis of the metamodel responsible for modeling the behaviour of the individuals involved in traffic previously introduced on previous publications. The case study validates the proposal through a first version of a simple system of sensors that check passing vehicles.
Associating Colors to Emotional Concepts Extracted from Unstructured Texts
This article introduces the development framework CALyPSe, which is responsible for generating colour palettes and abstract paintings. These are obtained applying Natural Language Processing (NLP) on texts. These are analysed through Freeling. Then, the lemmas of extracted words are associated to the feelings of people. To do that, these words are compared to a predetermined set of them which have certain colours associated. This colour relationships is provided by the literature related to the psychology of colour.
Enriched semantic graphs for extractive text summarization
This publication is focused on the creation of a development process responsible for generating automatic extractive summaries from texts written in Natural Language. To do that, it uses Freeling as the dependency parser and produces enriched semantic graphs (with syntactical and linguistic information) from the latter. Finally a clustering algorithm is applied in order to obtain the main topics of the analysed text. This allows generating the summary linking the most representative nodes of each cluster (hub nodes) with the main sentences.
Grafeno: Semantic Graph Extraction and Operation
This article introduces the Grafeno library which has been specially created for the Natural Language processing. Different operations are presented, such as the semantic extension of the identified topics in the semantic analysis and their classifications according to the results obtained by multiple clustering algorithms. Also, different graph integrations are illustrated, highlightining the conceptual maps and the enriched semantic graphs with syntactic and ligüistic information in their edges. All of these is addressed through a configurable pipeline using instructions provided by YAML.