The main contributions of this research include developing a light-weighted multiagent-based system for crowd simulation and modeling bounded rationality of the agents in such system. We deploy the belief-desire-intention (BDI) concept to model our agents. Whereas most works in the field assume perfect information, we take into account the bounded rationality characteristics of human beings into the perception of agents. We found that the increasing number of agents affects the performance by increasing duration, number of rounds, duration per round, duration per agent, and round per agent in two dense scenes. However, the perception process added on does not directly affect the performance of the algorithm. With regards to the behavior of the agents, we found that most agents are affected by the increasing number of agents that their paths divert significantly from the original plan. However, there are some agents which apparently can maintain their paths close to their original ones.
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