Thursday, March 17, 2011

Balancing Seven Carts

Single recurrent neural network (15 hidden neurons) evolved to balance seven double-pole carts simultaneously. No velocity information is available to the controller, so it is a non-Markovian task. For each of the seven carts, the controller has access to the cart position, and the angle of both poles, for a total of 21 inputs. The controller has seven outputs with which it applies force to the carts at each time step. The force is continuously valued, rather than "bang-bang".

It is able to successfully keep balance for 5000 time steps, although it becomes unstable at the end. The process of evolving the controller took precisely 13,373,736 fitness evaluations (roughly 20 hours of CPU time.)

This controller was, for the sake of time, only evolved on a single initial condition (with slightly off-center pole angles), so it is unknown how well it generalizes to other initial conditions. However, it still proves to be a very challenging task.

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