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» Learning Policies for Embodied Virtual Agents through Demons...
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JMLR
2002
125views more  JMLR 2002»
13 years 4 months ago
Lyapunov Design for Safe Reinforcement Learning
Lyapunov design methods are used widely in control engineering to design controllers that achieve qualitative objectives, such as stabilizing a system or maintaining a system'...
Theodore J. Perkins, Andrew G. Barto
BERTINORO
2005
Springer
13 years 10 months ago
Emergent Consensus in Decentralised Systems Using Collaborative Reinforcement Learning
Abstract. This paper describes the application of a decentralised coordination algorithm, called Collaborative Reinforcement Learning (CRL), to two different distributed system pr...
Jim Dowling, Raymond Cunningham, Anthony Harringto...
CHI
2009
ACM
14 years 5 months ago
Social immersive media: pursuing best practices for multi-user interactive camera/projector exhibits
Based on ten years' experience developing interactive camera/projector systems for public science and culture exhibits, we define a distinct form of augmented reality focused...
Scott S. Snibbe, Hayes Raffle
ALIFE
1998
13 years 5 months ago
Evolutionary Body Building: Adaptive Physical Designs for Robots
Creating artificial life forms through evolutionary robotics faces a “chicken and egg” problem: learning to control a complex body is dominated by problems specific to its s...
Pablo Funes, Jordan B. Pollack
NECO
2007
150views more  NECO 2007»
13 years 4 months ago
Reinforcement Learning, Spike-Time-Dependent Plasticity, and the BCM Rule
Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...
Dorit Baras, Ron Meir