This is the ODD-protocol of AgriPoliS with an Agent enhanced with Deep Reinforcement Learning

This document is based on the 2012 version of AgriPoliS ODD, restructured and updated.

An introduction to AgriPoliS following the ODD-protocol (Overview, Design concepts and Details). This includes the description of the model purpose, the entities and a process overview. Furthermore, it provides information about the basic applied principles and the initialization process.

Detailed documentation about AgriPoliS

This document focusses on the collection and compilation of input files for AgriPoliS. It describes the development of a virtual farm structure and the steps for modeling the farm agents.

This document is a deliverable of the IDEMA-project and contains a detailed documentation of AgriPoliS. That includes sections about the conceptual framework, the implementation of the conceptual model, input and output objectives, the involved agents and data input and output. Additionally, an explanation of how AgriPoliS is adapted to a case study region is provided. It also contains a description of the IDEMA case study regions.

Under this link you find the dissertation of Kathrin Happe. She describes how an agent-based model like AgriPoliS can be used to study agricultural policies and their effects on structural change in agriculture. The dissertation provides general information about agent-based models, meaning their motivation, definition and application. Then she provides a detailed documentation which includes sections about the conceptual framework, the implementation of the conceptual model, input and output objectives, the involved agents and data input and output. The dissertation includes a documentation of the adaptation of the region Hohenlohe to AgriPoliS. In the analysis section she shows simulation results of policy scenarios on retirement payment, phasing out and decoupled single farm payments.

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