Mixtures of Controllers for Jump Linear and Non-Linear Plants

Part of Advances in Neural Information Processing Systems 6 (NIPS 1993)

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Timothy Cacciatore, Steven Nowlan


We describe an extension to the Mixture of Experts architecture for modelling and controlling dynamical systems which exhibit multi(cid:173) ple modes of behavior. This extension is based on a Markov process model, and suggests a recurrent network for gating a set of linear or non-linear controllers. The new architecture is demonstrated to be capable of learning effective control strategies for jump linear and non-linear plants with multiple modes of behavior.