The objective of this article is to review how Artificial Intelligence (AI) tools have helped the process of formulating agricultural public policies in the world. For this, a search process was carried out in the main scientific repositories finding different publications. The findings have shown that, first, the most commonly used AI tools are agent-based models, cellular automata, and genetic algorithms. Secondly, they have been utilized to determine land and water use, and agricultural production. In the end, the large usefulness that AI tools have in the process of formulating agricultural public policies is concluded.

The purpose of this article consists of analyzing publications discussing the use of agent-based artificial intelligence models in sustainable agriculture research. The analysis involved bibliometric indicators and the Rstudio software with Bibliometrix library. The methodology is descriptive with a quantitative approach. Scientific databases SCOPUS and Web of Science were consulted and the PRISMA methodology was used during the selection process. This led to finding 86 publications that met the inclusion criteria. Amongst the results, United States was listed as the country with the highest production of scientific material, although France had a higher impact. Additionally, the bibliographical resources that help promote scientific development are open source. It was concluded that the agent-based model has been adopted to simulate different scenarios, which help decision-makers to formulate public policies in favor of sustainable agriculture. This optimizes the use of natural resources and reduces negative consequences for the environment, while also delivering value for the stakeholders of the agricultural system.

Floods are one of the worst natural disasters in the world. Colombia is a country that has been greatly affected by this disaster. For example, in the years 2010 and 2011 there was a heavy rainy season, which caused floods that affected at least two million people and there were economic losses of 6.5 million dollars, which is equivalent to 5.7% of the country's Gross Domestic Product (GDP) at that time. The Magdalena River is the most important since 128 municipalities and 43 cities with a population of 6.3 million people, which is 13% of the total population of the country, are located in its basins. For this reason, the objective of the research is to design and implement a model that helps predict flooding over the Magdalena River by examining three techniques of artificial intelligence (Artificial Neuronal Networks, Adaptive Neuro Fuzzy Inference System, Support Vector Machine), and thus determining which of these techniques are the most effective according to the case study. The research was limited only to these three types, due to limitations of time, data, human and financial resources, and technological infrastructure. In the end, it is concluded that the Artificial Neural Networks technique is a suitable option to implement the predictive system as long as it is not very complex and does not require high processing machine. However, to establish a model based on rules to achieve a better interpretability of the floods, the ANFIS model can be used.

El objetivo de este artículo es analizar las publicaciones científicas especializadas en el uso de herramientas de inteligencia artificial en el proceso de toma de decisiones durante la formulación de políticas públicas. Como herramienta metodológica se creó una ecuación de búsqueda para ubicar las publicaciones concernientes, la cual fue probada y perfeccionada varias veces para mejorar los resultados encontrados. Esta ecuación fue aplicada en la base de datos de Scopus, con lo cual se obtuvieron 1154 publicaciones, a las que se aplicaron indicadores bibliométricos. En los resultados obtenidos se encontró que principalmente esta área ha tenido un gran crecimiento en la última década; cuyos países con mayor producción son: Estados Unidos, República Popular de China y el Reino Unido. Al comparar producción científica con las entidades patrocinantes se pudo concluir la importancia del apoyo gubernamental para desarrollo científico de un país. The objective of this article is to analyze the scientific publications made regarding the use of artificial intelligence tools in the decision-making process in the formulation of public policies. The methodology used was initially to create a search equation to locate the publications in this regard, which was tested and refined several times to improve the results found, this equation was applied in the SCOPUS database, with which 1.154 publications were obtained, to which bibliometric indicators were applied. The main results obtained were that this area has had great growth in the last decade, where the countries with the highest production are the United States, the People's Republic of China and the United Kingdom. By comparing scientific production with financing entities, it was possible to conclude the importance of government support for scientific development in a country.

Context: The process of formulating agricultural public policies is very complex due to the large number of variables involved in the process. That is why the development of decision support systems (DSS) help to improve this process. The article reviews the developments that have been made regarding the subject. Method: The method was to conduct a bibliographic review in several scientific databases, looking for developments of DSS systems applied to the process of formulating agricultural policies. When determining which DSS systems have been developed, a qualitative and descriptive analysis of the systems was carried out.

El objetivo de este trabajo fue realizar una revisión sobre el uso de las técnicas de inteligencia artificial (IA) aplicadas a la formulación de políticas públicas que contribuyan a la vocación agrícola de las regiones, para lo cual se usó una metodología descriptiva con enfoque mixto. El diseño metodológico utilizado fue el PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Las publicaciones analizadas fueron tomadas de la base de datos de Scopus. Para el análisis cuantitativo se utilizaron las herramientas informáticas VosViewer y la librería Bibliometrix del lenguaje R. Como resultado se encontró que las técnicas de IA se han aplicado para identificar zonas con vocación agrícola o para encontrar mejores prácticas agrícolas que promuevan el desarrollo sostenible. Se concluyó que esta área de investigación es incipiente y que es necesario generar nuevos modelos que sean más robustos e incluyan variables demográficas, sociales, ambientales, económicas y políticas. The objective of this work was to conduct a review on the use of artificial intelligence (AI) techniques applied to the formulation of public policies that contribute to the agricultural vocation of the regions. To this effect, a descriptive methodology with a mixed approach was employed. The methodological design used was PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). The analyzed publications were taken from the Scopus database. For the quantitative analysis, the VosViewer software and the Bibliometrix R language library were used. As a result, it was found that AI techniques are employed to identify areas with an agricultural vocation or to find better agricultural practices that promote sustainable development. It was concluded that this research area is incipient and that it is necessary to generate new models that are more robust and include demographic, social, environmental, economic, and political variables.