Performance Analysis of the Jason Reasoning Cycle

Jason is a popular interpreter of AgentSpeak(L) that provides an environment to develop and run autonomous agents. We are interested in determining if Jason can be used to develop autonomous robots that can be run on modern hardware. To this end, we determined the time complexity of each of the ten steps of the Jason reasoning cycle and used that complexity to help us identify what parameters could be changed to have the biggest effect on the execution time of the reasoning cycle. We also generate a model to predict future performance. We validate this model using three different case studies, comparing the predicted execution times to those we measure. We find that our developed model consistently predicted an execution time one order of magnitude higher than the measured execution time for each case study. We further find that, using modern hardware, Jason provides a suitable environment for autonomous robots.