Better modeling for Homo Economus

Using a single motivation as the basis for all human behavior, as classical economic theory does, would necessarily be a little limiting. One can see the necessity of doing this in the 19th century, as it made the mathematics tractable, but in the present it obviously is too limited. A computer simulation can obviously model a much more complex structure of human motivations. I am visualizing a pool of several thousand agents that would model a market. They would make decisions based on two scores, one of which would determine tolerance for risk, the other would determine the degree to which they would grasp for reward. Both scores are calculated by having all the agents in the simulation exchange tokens with each turn. The first calculates public mood, or what everyone "thinks" about the situation being modeled. All the agents have an internal token reflecting what they "think" about the situation. They trade tokens with all other agents accessible to them in the situation being modeled. At the end of the turn, the tokens will be averaged and combined with the value of the internal token. Introvert agents will take 90% internal token, and 10% external average, extrovert agents will take 10% internal token and 90% external token. The value will then be loaded into the internal token for the next round. A pool of agents who take a 50/50 split could be set up as well with the usual normal distribution 16% / 68% / 16%, even though perfect balance personalities are probably extremely rare. The pools of agents could then be adjusted until the simulation behaves something like real life.  Also, rather than greed being the fundamental human motivation, I would propose jealousy. In order to add this to the simulation, a second internal token will be added to each agent. This token will record how far above or below the average the agent finds itself to be. Each turn all agents that are directly connected will exchange tokens of their perceived economic state. Introverted agents will exchange with a smaller pool than extroverted agents. All agents will receive information from the total pool as a somewhat randomized average to reflect the influence of the media. The pair of tokens will be used to determine whether the agent will buy or sell when presented with opportunities in the model. The first determines response to risk, the second, motivation to acquire. I would expect a pool of several thousand of these agents to behave much more like a group of humans in a market than a simulation based of classical economics would, and yet be easily simulated.