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IAT
2010
IEEE
13 years 1 months ago
A Biologically-Inspired Cognitive Agent Model Integrating Declarative Knowledge and Reinforcement Learning
Abstract--The paper proposes a biologically-inspired cognitive agent model, known as FALCON-X, based on an integration of the Adaptive Control of Thought (ACT-R) architecture and a...
Ah-Hwee Tan, Gee Wah Ng
IROS
2006
IEEE
190views Robotics» more  IROS 2006»
13 years 9 months ago
Q-RAN: A Constructive Reinforcement Learning Approach for Robot Behavior Learning
Abstract— This paper presents a learning system that uses Qlearning with a resource allocating network (RAN) for behavior learning in mobile robotics. The RAN is used as a functi...
Jun Li, Achim J. Lilienthal, Tomás Mart&iac...
NIPS
1996
13 years 5 months ago
Reinforcement Learning for Mixed Open-loop and Closed-loop Control
Closed-loop control relies on sensory feedback that is usually assumed to be free. But if sensing incurs a cost, it may be coste ective to take sequences of actions in open-loop m...
Eric A. Hansen, Andrew G. Barto, Shlomo Zilberstei...
ICRA
1994
IEEE
94views Robotics» more  ICRA 1994»
13 years 7 months ago
A Reinforcement-Learning Approach to Reactive Control Policy Design for Autonomous Robots
Within the field of robotics, much recent attention has been given to control techniques that have been termed reactive or behavior-based. The design of such control systems for e...
Andrew H. Fagg, David Lotspeich, George A. Bekey
WSC
2007
13 years 6 months ago
Optimizing time warp simulation with reinforcement learning techniques
Adaptive Time Warp protocols in the literature are usually based on a pre-defined analytic model of the system, expressed as a closed form function that maps system state to cont...
Jun Wang, Carl Tropper