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CCIA
2005
Springer
13 years 11 months ago
Direct Policy Search Reinforcement Learning for Robot Control
— This paper proposes a high-level Reinforcement Learning (RL) control system for solving the action selection problem of an autonomous robot. Although the dominant approach, whe...
Andres El-Fakdi, Marc Carreras, Narcís Palo...
ICML
2009
IEEE
14 years 6 months ago
Binary action search for learning continuous-action control policies
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
Jason Pazis, Michail G. Lagoudakis
NIPS
2003
13 years 7 months ago
Bounded Finite State Controllers
We describe a new approximation algorithm for solving partially observable MDPs. Our bounded policy iteration approach searches through the space of bounded-size, stochastic fini...
Pascal Poupart, Craig Boutilier
CPAIOR
2007
Springer
14 years 7 days ago
Replenishment Planning for Stochastic Inventory Systems with Shortage Cost
One of the most important policies adopted in inventory control is the (R,S) policy (also known as the “replenishment cycle” policy). Under the non-stationary demand assumption...
Roberto Rossi, Armagan Tarim, Brahim Hnich, Steven...