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It has long been established that simulation is a powerful tool for aiding decision making. This is due to a number of factor, such as the inherent ability to evaluate complex systems with large number of variables and interactions for which there is no analytical solution. It is considered as a tool to answer “what if” questions, not a solution generator technique. This scenario could be changed with the aid of optimization procedures, and so simulation could answer not only “what if” questions but also answers “how to” questions, providing the best set of input variables and maximize or minimize some performance measure. For the purposes of optimization, the simulation is simply a “black box” which computes a realization of the (stochastic) function value for a given combination of the parameter values (Magoulas et al., 2002). Simulation optimization is the process of finding the best values of some decision variables for a system where the performance is evaluated based on the output of a simulation model of this system. The components of a typical optimization system are present in a simulation optimization system: decision variables, objective function and constraints. The decision variables must be contained in some feasible region defined by the constraints. The objective function is a real valued function defined on these variables, but due to the complexity and stochastic nature of the underlying system an analytical expression can not be determined and the value returned by the stochastic simulation must be used instead. The predator-prey game is a multi-agent system, which originally came from the field of Artificial Intelligence (AI). At first, this field was called Distributed Artificial Intelligence (DAI); instead of reproducing the knowledge and reasoning of one intelligent agent as in AI, the objective became to reproduce the knowledge and reasoning of several heterogeneous agents that need to jointly solve planning problems. Some researchers have focused more on the agent and its autonomy (for instance, the definition of an agent proposed by Wooldridge and Jennings (1999): “an agent is a computer system that is situated in some environment, and that is capable of autonomous action in this environment in order to meet its design objectives”), while others, engaged in the field of multi-agent systems, have focused more on the organization of multiple agent interactions (Huhns & Stephens, 1999). The aiming of this work is to propose a simulation optimization tool for solutions' synthesis to a problem involving a dynamic and complex system (to bring forth strategies for a

Simulation Optimization Using Swarm Intelligence as Tool for Cooperation Strategy Design in 3D Predator-Prey Game