The validation of agent-based simulation is quite important to convince the results to various audiences. To address the issues, we have developed a new agent-based simulation environment using Genetic Algorithms (GAs). The basic principles are summarized as follows: (1) Set various agent parameters as an individual of GAs; (2) Run the agent-based model in parallel so that the runs form the population of GAs; (3) Based on a given criteria or an objective function, each simulation result is evaluated; (4) Genetic operators are then applied to generate the other set of agent parameters; and (5) After the convergence or when we have 'desired' results, the variances among the parameters are evaluated to validate the results in the sense of the sensitivity analyses. TRURL is such a simulation environment, which evolves artificial worlds of multiagents to socially interact with each other. The agents in TRURL solve simple multi-attribute decision problems via the message communication among them. The micro-level agent activities are determined by both predetermined and acquired parameters. The former parameters have constant values during one simulation epoch, however, the latter parameters change during the interactions. TRURL utilizes the above principles to evolve the societies by changing the predetermined parameters to optimize macro-level socio-metric measures, which can be observed in such real societies as e-mail oriented organizations and electronic commerce markets. Thus, using TRURL, we automatically tune the parameters up and validate the results from both micro- and macro-level phenomena grounding on the activities of real worlds.
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