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Multi-Agent Systems (MASs) are often used to optimize the use of the resources available in an environment. A flaw during the modelling phase or an unanticipated scenario during their execution, however, can make the agents behave not as planned. As a consequence, the resources can be poorly utilized and operate sub-optimized, but it can also bring the resources into an unexpected state. Such problems can be mitigated if there is a controlled environment to test the agents’ behaviour before deployment. To this end, a simulated environment provides not only a way to test the agents’ behaviour under different common scenarios but test them as well in adverse and rare state conditions. With this in mind, we have developed ARPS, an open-source framework that can be used to design computational agents, evaluate them in a simulated environment modelled after a real one, and then deploy and manage them seamlessly in the actual environment when the results of their evaluation are satisfactory.