Bounded Finite State Controllers

Part of Advances in Neural Information Processing Systems 16 (NIPS 2003)

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Pascal Poupart, Craig Boutilier


We describe a new approximation algorithm for solving partially observ- able MDPs. Our bounded policy iteration approach searches through the space of bounded-size, stochastic finite state controllers, combining sev- eral advantages of gradient ascent (efficiency, search through restricted controller space) and policy iteration (less vulnerability to local optima).