Chapter 9 Agent-Based Modelling of Social Capital and
Destructive Fishing
9.1 Introduction
Advancement in computer tools opens up opportunity to investigate and simulate the interactions of diverse actors in a specific environment, as well as
the interactions between ecological and social components. This approach is known as agent-based modelling. It relies on a bottom-up approach, through
modeling of agents’ behavior and interactions. Several authors have been using agent-based modelling in the field of ecosystem management, such as water
management, fisheries management, park management, archeological issues, lake management, and agricultural land management Bousquet and Le Page
2004. The application on coral reefs management is yet to be studied. This chapter presents the multi-agent simulations of destructive fishing
social capital. This simulation experiment is a preliminary approach to understand the dynamics underlying social capital. In particular, its aim is to test the
assumptions about how social capital in the form of fisher’s sanction influences the destructive fishing. Specifically, it is appealing to investigate in which
conditions of market price, fish biomass, and production cost that social capital influences the destructive fishing. A computer-based modelling strategy allows
experimentation of the dynamics between social interaction and ecosystem. The model building consists of fishers as the agents and fish biomass as the
ecosystem. The analysis in this chapter makes use of simulation, a computer-based
modelling strategy that allows experimentation with dynamic networks. An agent- based modelling is built in order to test the following:
1. To what extent social capital in the form of fisher’s sanction influences the destructive fishing.
2. To what extent the conditions of market price, fish biomass, and production cost influence the way social capital affects destructive fishing.
There is now a growing literature studying various phenomena using the ‘bottom up’ technique of artificial agent based modeling. This approach is also
known as multi-agent systems or multi-agent simulations MAS. MAS are systems in which agents are distributed in an artificial environment and are able
to interact with each other andor with the environment in a parallel fashion Bailón 2004; Bousquet and Le Page 2004. In the model, agents are created,
which are entities of the artificial world. On the other hand, actors are people in the real world Bousquet et al. 1999.
MAS take a bottom up approach to generating data comparable to that observable in the real system. This bottom up approach gives attention to writing
instructions to specify the behavior of the individual components parts of the real world system that is being studied. There are two basic components of the
intelligent agents, namely a model of agents and a model of their environment. A model of agents contains the instructions for generating the behavior of the agent
under different situation. On the other hand, a model of the environment is the world in which the agents exist. The overall behavior emerges as a result of the
actions and interactions of the individual agents. At this point, observations of the results can be assessed Deadman 1999.
9.2 Simulation Experiment