GOAL-DTU: Development of Distributed Intelligence for the Multi-Agent Programming Contest

We provide a brief description of the GOAL-DTU system for the agent contest, including the overall strategy and how the system is designed to apply this strategy. Our agents are implemented using the GOAL programming language. We evaluate the performance of our agents for the contest, and finally also discuss how to improve the system based on analysis of its strengths and weaknesses.Comment: 28 pages, 45 figure

The Regional Multi-Agent Simulator (RegMAS): an open-source spatially explicit model to assess the impact of agricultural policies

RegMAS (Regional Multi Agent Simulator) is an open-source spatially explicit multi-agent model framework specifically designed for long-term simulations of the effects of policies on agricultural systems. Using iterated conventional optimisation problems as agents’ behavioural rules, it allows for a bidirectional integration between geophysical and social models where spatially-distributed characteristics are taken into account in the programming problem of the optimising agents. With RegMAS it is possible to simulate the local specific response to a given policy (or scenario), where policies, together with macro and regional characteristics, are read into the program in specially formatted spreadsheets and standard GIS files. The paper presents the model logic and structure and describes its functioning by applying it to a case-study, where RegMAS results are compared with conventional agent-based modelling to demonstrate the advantages of spatial explicitness. The simulation refers to the impact of the recent “Health Check” of the CAP on farm structures, income and land use in a hilly area of a central Italian region (Marche).Agent-Based Modelling; Mathematical Programming; Explicit Spatial Analysis; Common Agricultural Policy