Ejercicios teóricos y prácticos para contribuir al mejoramiento del pensamiento táctico de los pasadores escolares

El pensamiento táctico es un factor determinante en el resultado del juego, por lo que se hace cada vez más necesario su puesta en práctica en cada uno de los choques que se realicen, ya sean de entrenamiento, topes o competencias, el entrenador debe conocer donde radican las principales deficiencias tácticas del equipo con vista a dirigir su trabajo para solucionar estos problemas La investigación tuvo como objetivo un sistema de ejercicios teóricos y prácticos para el desarrollo del pensamiento táctico de pasadores escolares de la categoría 13-15 años masculinos de la Eide "Cerro Pelado" de Camagüey. Se utilizaron varios métodos y técnicas de investigación: teóricos, empíricos y estadísticos. El diagnóstico permitió verificar el proceso del desarrollo del pensamiento táctico donde se devela como principal insuficiencia, dificultad en la ejecución de los pasadores en lo técnico-táctico evidenciando poca efectividad de ejecución, solución de situaciones y problemas táctico durante el entrenamiento y competencia. El sistema de ejercicios incluye acciones individual y grupal en pasadores

MSGLib: A Modelica library for message passing communication

MSGLib is a Modelica library designed and developed to support message passing communication and the management of data structures stored in dynamic memory. The functionality of the library facilitates the description of discrete-event models and their combination with other Modelica functionality. MSGLib has been used as a base to develop other Modelica libraries such as DEVSLib, ARENALib and ABMLib. A new version of MSGLib is presented in this manuscript, that includes user documentation, performance optimization and illustrative examples. The library has been developed and tested under Dymola and OpenModelica, and is freely distributed under the LGPL-3.0 license

An approach to agent-based modeling with Modelica

Modelica is a free, general-purpose object-oriented equation-based modeling language. It is mainly designed to describe systems using the physical modeling approach. Our proposal to describe Agent-Based Models (ABMs) in Modelica is discussed in this manuscript. The contribution of the presented work is twofold: firstly, to analyze the conceptual requirements to describe ABMs in Modelica; and secondly, to develop a prototype implementation following the previous analysis. Agents are described using a message passing communication mechanism previously proposed by the authors. Additional extensions to this mechanism are proposed in order to describe agent interactions. The environment, where the agents live, is described as a two-dimensional cellular automaton. A new Modelica library, named ABMLib, developed to support this functionality, is presented. A prototype implementation of the message passing mechanism and ABMLib models has been performed to demonstrate the functionality of the library as a proof-of-concept for this proposal.Fil: Sanz, Victorino. Universidad Nacional de Educación a Distancia; EspañaFil: Bergero, Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Urquia, Alfonso. Universidad Nacional de Educación a Distancia; Españ

CellularAutomataLib2: improving the support for cellular automata modelling in Modelica

CellularAutomataLib is a library developed by the authors to facilitate the description of Cellular Automata (CA) models in Modelica. It supports the description of 1D and 2D CA and their combination with other Modelica models. Modelling versatility and scalability are the main focus in the design. The internal behaviour of CA models is programmed in C, that is consequently hidden to the modelling tool and not considered in the causalization and manipulation of the model. A new version, named CellularAutomataLib2, is presented in this manuscript. The library has been extended to improve the simulation performance, by only evaluating active cells, and to support Lattice Gas Cellular Automata (LGCA) models. The library design and use are discussed. Two models, forest fire spread and the ARGESIM C17 ‘SIR-type Epidemic Spread’, are used to illustrate the functionality of the library. CellularAutomataLib2 is freely available at http://www.euclides.dia.uned.es (under the Modelica License 2)