Intelligent agents designed to perform in the real world should by definition be tested and evaluated in the real world. However, this is impossible in many situations. A lack of resources may rule out construction of a complete robotic environment for example, or the desired domain may be physically inaccessible for testing. In such situations, the use of a simulation system to provide an environment in which to test and examine the intelligent system is necessitated. In the past, such systems have acquired a poor reputation within the artificial intelligence community, mainly due to the sometimes grandiose claims of systems that are tested solely under simulated conditions. In this paper the conditions under which simulation is justified are explored: the inadequacies of currently available systems for the testing and examination of intelligent agents are examined; and Gensim, a new system designed to address these inadequacies, is described. Rather than providing a single, parameterized domain, Gensim provides a collection of facilities allowing users to design complete environments for examining and testing intelligent agents. The system also provides a clean interface, allowing widely differing types of agents to be studied. While some bias is unavoidable, these facilities are designed to be as widely applicable as possible.