A hybrid controller based on the egocentric perceptual principle

In this paper we extend the control methodology based on Extended Markov Tracking (EMT) by providing the control algorithm with capabilities to calibrate and even partially reconstruct the environment’s model. This enables us to resolve the problem of performance deterioration due to model incoherence, a problem faced in all model-based control methods. The new algorithm, Ensemble Actions EMT (EA-EMT), utilises the initial environment model as a library of state transition functions and applies a variation of prediction with experts to assemble and calibrate a revised model. By so doing, this is the first hybrid control algorithm that enables on-line adaptation within the egocentric control framework which dictates the control of an agent’s perceptions, rather than an agent’s environment state. In our experiments, we performed a range of tests with increasing model incoherence induced by three types of exogenous environment perturbations: catastrophic – the environment become...

• Type: Journal
• Year: 2010
• Where: RAS
• Authors: Zinovi Rabinovich, Nicholas R. Jennings
• Keywords: Initial Environment Model, Model, Model Incoherence, RAS 2010