Simsea: A Multiagent Architecture For Fishing Activity In A Simulated Environment

Understanding fishermen decision-making proccess, plays a key role in predicting the impacts of the fishing activity in the marine ecosystems. Simulating fishing activity using multiagent based approaches provides tools that assist decision-makers in order to pursuit sustainable fishing activity. In this paper we present a multiagent architecture for the fishing activity where geo-referenced resources and fishing agents with different profiles are used to model and simulate the complexity of human fishing activity. A first implementation of the model (via NetLogo), along with gathered results, provides insights into the capability to build a research tool for fisheries management.