Towards teaching Artificial Intelligence using a Model-Driven approach
In computer science, it is quite difficult to teach well an introductory course on AI,partly because AI lacks a unified methodology, overlaps with many other disciplines, and involves a wide range of skills from very applied to quite formal. When teaching Artificial Intelligence, models are the prin...
| Autores: | , , , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2013 |
| País: | Argentina |
| Recursos: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/6423 |
| Acesso em linha: | http://hdl.handle.net/11336/6423 |
| Access Level: | acceso abierto |
| Palavra-chave: | Inteligencia Artificial Educacion https://purl.org/becyt/ford/1.2 https://purl.org/becyt/ford/1 |
| Resumo: | In computer science, it is quite difficult to teach well an introductory course on AI,partly because AI lacks a unified methodology, overlaps with many other disciplines, and involves a wide range of skills from very applied to quite formal. When teaching Artificial Intelligence, models are the principal artifacts used by professors to communicate concepts. These models should be used as part of a technical answer of a practical work, with the aim of narrowing the distance between concepts and their implementation in a programming language. The model-driven development presents a very promising approach to reduce the difficulties in the generation of code solutions. This work presents an MDD-based method, a language to define intelligent agent and a computational tool that gives support to the MDDbased method. |
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