  We propose an adaptive model-predictive controller that balances driving the
system to a goal state and seeking system observations that are informative
with respect to the parameters of a nonlinear autoregressive exogenous model.
The controller's objective function is derived from an expected free energy
functional and contains information-theoretic terms expressing uncertainty over
model parameters and output predictions. Experiments illustrate how parameter
uncertainty affects the control objective and evaluate the proposed controller
for a pendulum swing-up task.
