Using institutional arrangements and hybrid automata for regional scale agent-based modelling of land change

This paper discusses the use of agent-based models for capturing land change in large frontier areas. Applying agent models in such areas is not straightforward, given the lack of data. To date, most agent based models of land frontiers study local areas using in-situ information. At regional scales, agent-based modellers need additional ways to describe collective decision-making. This paper presents two ideas to deal with the complexities of agent-based models at such scales: institutional arrangements and hybrid automata. Institutional arrangements help to model multiagent interaction by explaining why, although there are rules and norms for land use, these rules are not always followed. A hybrid automaton combines a discrete state machine with continuous actions inside a state. This formalism captures states and transitions of agents in a simulation and helps to build expressive models. We validate our ideas by building a deforestation model in an area of 200,000 km in Amazonia. Results show that we need to set different arrangements to capture changes in agents’ behaviour, as they react to external conditions. Thus, combining the ideas of institutional arrangements and hybrid automata improves the explanatory power of agent models for regional scales.