PhD Progress: Results Update

The experiment is nearly complete for the Pacman with Population Constant 10, though the other two are still a long way from total completion. Each run has completed at least twice, though the Pop Const 10 has completed 8 runs.

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Judging by the speed of each experiment, the Pacman Pop Const 30 takes roughly as long as the 50, which is interesting as they share the same results. The question is, which approach is best? The Pop Const 10 does eventually match the other two performances, and will likely level out just as the others did. But it can reach the goal in less time, but more learning iterations. I suppose in the end, all are judged by time, as the number of iterations can be infinite, if necessary. So perhaps this Pop 10 works, but should have a larger number of iterations to learn over.

Note that these results are using purely pre-goal specialisation only, no general rule specialisation. That still needs some work before I am ready to launch an experiment for that.

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