The underlying models and logic which define the fields of fuel game have been developed through an iterative process which involved agronomists, biofuel experts, ecologists, and computer scientists. While the game model is not perfect, it closely represents the current state of scientific understanding around these systems does what we consider an excellent job at describing the dynamics and interactions of the various components. In an effort to be as transparent as possible during this process, we have exposed all of the underlying logic that drives the game, including how the scoring is implemented. Detailed information on these aspects can be found in the links below.
Quantifying the concept of sustainability is an inherently difficult process. However, a large part of games and learning involves receiving clear and targeted feedback on player performance. In order to facilitate this, we have tried to develop a rigorous and objective scoring system based on the concept that sustainability consists of three primary components; economic, environmental, and social. In this game we use the concept of energy production as a surrogate for social impact, as energy production is closely related to general welfare, and is a much more tangible element in our system. Each player is evaluated and scored on a range from zero to 100% on each of these elements, with higher scores reflecting better performance. Players are ranked by score in different categories, depending on what the predefined game objective is. Ranks are determined by comparing each players score in the different categories over the duration of gameplay. The overall sustainability score is a weighted average of those three scores. The detailed description of these scores can be found on the scoring page.
In an effort to represent this system as accurately as possible, building the underlying logic that dictates the game logic has involved a diverse range of experts. Personnel from various academic fields were consulted for development, testing, and refining of the various components that make up this logic. The result is a robust game model that we think does an excellent job at reflecting the various dynamics of biofuel cropping systems in a way that is accurate and accessible. The core of this logic involves the development of three model systems that reflect the three relevant sub-components of the game: economy, energy, and environment. A brief overview of each with links to the models specifics are found below.
The economic model has two parts; an accounting feature that determines the costs of agricultural productions at the farm level, and an optional dynamic market that determines crop prices (by default this is off, and prices are static). The agricultural production costs are derived from a range of sources, and reflect the specific cropping and management strategies employed by the player. The dynamic market, when enabled, uses a constant elasticity of supply model to set prices in an attempt to balance supply and demand for both a feed and fuel market. More information on the economic models can be found on the Economy Model page.
The energy model also uses an accounting model that tracks the energy usage of different inputs specified by the players choices, including aspects such as fertilizer production and application, tillage, harvesting, and transportation. The accounting model also extends to the refinement of crops into fuel, and incorporates the different energy requirements and yields for different types of crops. A more in-depth description can be found in the Energy Model page.
The environment is reflected with a suite of models that incorporates four different measures of environmental health; soil fertility, insect diversity, CO2 emissions, and nitrogen leaching. Many of these models have various interactions, making them very difficult for players to manipulate individually; for example, insect diversity on your farm is influenced by your neighbors decisions, and nitrogen leaching is a function of cropping decisions applied within the context of the soil fertility of a specific field, driven by a detailed nitrogen cycling model. More information on these components can be found on the Environment models page.