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» Using Learning in a Control Agent
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ICWS
2004
IEEE
15 years 8 months ago
Access Control for Semantic Web Services
In this paper we make a contribution to the proof and trust layer of the Semantic Web layer cake by integrating two well founded techniques, namely DAML-S (for describing Web serv...
Sudhir Agarwal, Barbara Sprick
ICAART
2010
INSTICC
16 years 3 months ago
Complexity of Stochastic Branch and Bound Methods for Belief Tree Search in Bayesian Reinforcement Learning
There has been a lot of recent work on Bayesian methods for reinforcement learning exhibiting near-optimal online performance. The main obstacle facing such methods is that in most...
Christos Dimitrakakis
ICCBR
2005
Springer
16 years 7 days ago
CBR for State Value Function Approximation in Reinforcement Learning
CBR is one of the techniques that can be applied to the task of approximating a function over high-dimensional, continuous spaces. In Reinforcement Learning systems a learning agen...
Thomas Gabel, Martin A. Riedmiller
GECCO
2003
Springer
126views Optimization» more  GECCO 2003»
15 years 12 months ago
Coevolution and Linear Genetic Programming for Visual Learning
In this paper, a novel genetically-inspired visual learning method is proposed. Given the training images, this general approach induces a sophisticated feature-based recognition s...
Krzysztof Krawiec, Bir Bhanu
IJON
2002
154views more  IJON 2002»
15 years 6 months ago
Nonlinear model predictive control of a cutting process
Nonlinear model predictive control (MPC) of a simulated chaotic cutting process is presented. The nonlinear MPC combines a neural-network model and a genetic-algorithm-based optim...
Primoz Potocnik, Igor Grabec