Practical Solution Techniques for First-order MDPs ⋆ Scott Sanner ∗ Statistical Machine Learning Group National ICT Australia Canberra, ACT, 0200, Australia

First Page		Document Content
Date: 2008-11-29 09:22:37 Operations research Control theory Equations Mathematical optimization Stochastic control Reinforcement learning Markov decision process Bellman equation Automated planning and scheduling Statistics Mathematics Dynamic programming		Practical Solution Techniques for First-order MDPs ⋆ Scott Sanner ∗ Statistical Machine Learning Group National ICT Australia Canberra, ACT, 0200, Australia Add to Reading List Source URL: users.cecs.anu.edu.au Download Document from Source Website File Size: 703,21 KB Share Document on Facebook

	Third Call for Papers TOPICS 21st International Conference on System Theory, Control and DocID: 1vrw3 - View Document
	A Dynamic Field Theory Based Pilot Model To Control Aircraft Pitch Attitudes Yasin Kaygusuz () TAI, Turkish Aerospace Industries, Fethiye Mah., Havacılık blv. No17, Akıncı, Kazan 06980, Ankara, Tu DocID: 1vmTp - View Document
	New Mathematical Tools in Reach Control Theory by Melkior Ornik DocID: 1vm3Q - View Document
	IMPLICIT DISCRETIZATION IN SLIDING-MODE CONTROL: THEORY AND EXPERIMENTS IMPLICIT DISCRETIZATION IN SLIDING-MODE CONTROL: THEORY AND EXPERIMENTS Bernard Brogliato, INRIA Grenoble DocID: 1v4sN - View Document
	References Summer School on Time Delay Equations and Control Theory Dobbiaco, June 25– DocID: 1uZZa - View Document