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QEST
2006
IEEE
15 years 12 months ago
Compositional Performability Evaluation for STATEMATE
Abstract— This paper reports on our efforts to link an industrial state-of-the-art modelling tool to academic state-of-the-art analysis algorithms. In a nutshell, we enable timed...
Eckard Böde, Marc Herbstritt, Holger Hermanns...
FLAIRS
2004
15 years 7 months ago
State Space Reduction For Hierarchical Reinforcement Learning
er provides new techniques for abstracting the state space of a Markov Decision Process (MDP). These techniques extend one of the recent minimization models, known as -reduction, ...
Mehran Asadi, Manfred Huber
ICRA
2010
IEEE
143views Robotics» more  ICRA 2010»
15 years 4 months ago
Apprenticeship learning via soft local homomorphisms
Abstract— We consider the problem of apprenticeship learning when the expert’s demonstration covers only a small part of a large state space. Inverse Reinforcement Learning (IR...
Abdeslam Boularias, Brahim Chaib-draa
VTC
2008
IEEE
152views Communications» more  VTC 2008»
16 years 10 days ago
Network Controlled Joint Radio Resource Management for Heterogeneous Networks
Abstract— In this paper, we propose a way of achieving optimality in radio resource management (RRM) for heterogeneous networks. We consider a micro or femto cell with two co-loc...
Marceau Coupechoux, Jean Marc Kelif, Philippe Godl...
ROBOCUP
2007
Springer
99views Robotics» more  ROBOCUP 2007»
16 years 2 days ago
Instance-Based Action Models for Fast Action Planning
Abstract. Two main challenges of robot action planning in real domains are uncertain action effects and dynamic environments. In this paper, an instance-based action model is lear...
Mazda Ahmadi, Peter Stone