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ATMOS
2007
177views Optimization» more  ATMOS 2007»
13 years 9 months ago
Approximate dynamic programming for rail operations
Abstract. Approximate dynamic programming offers a new modeling and algorithmic strategy for complex problems such as rail operations. Problems in rail operations are often modeled...
Warren B. Powell, Belgacem Bouzaïene-Ayari
AAMAS
2006
Springer
13 years 8 months ago
An Evolutionary Dynamical Analysis of Multi-Agent Learning in Iterated Games
In this paper, we investigate Reinforcement learning (RL) in multi-agent systems (MAS) from an evolutionary dynamical perspective. Typical for a MAS is that the environment is not ...
Karl Tuyls, Pieter Jan't Hoen, Bram Vanschoenwinke...
ICCV
2001
IEEE
14 years 10 months ago
Topology Free Hidden Markov Models: Application to Background Modeling
Hidden Markov Models (HMMs) are increasingly being used in computer vision for applications such as: gesture analysis, action recognition from video, and illumination modeling. Th...
Bjoern Stenger, Visvanathan Ramesh, Nikos Paragios...
ATAL
2007
Springer
14 years 2 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone
FGR
2000
IEEE
128views Biometrics» more  FGR 2000»
14 years 12 days ago
Understanding Purposeful Human Motion
Human motion can be understood on many levels. The most basic level is the notion that humans are collections of things that have predictable visual appearance. Next is the notion...
Christopher Richard Wren, Brian P. Clarkson, Alex ...