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FUZZIEEE
2007
IEEE
15 years 4 months ago
Fuzzy Approximation for Convergent Model-Based Reinforcement Learning
— Reinforcement learning (RL) is a learning control paradigm that provides well-understood algorithms with good convergence and consistency properties. Unfortunately, these algor...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...
AUSAI
2008
Springer
14 years 12 months ago
Using Gaussian Processes to Optimize Expensive Functions
The task of finding the optimum of some function f(x) is commonly accomplished by generating and testing sample solutions iteratively, choosing each new sample x heuristically on t...
Marcus R. Frean, Phillip Boyle
CDC
2008
IEEE
150views Control Systems» more  CDC 2008»
15 years 4 months ago
Subgradient methods and consensus algorithms for solving convex optimization problems
— In this paper we propose a subgradient method for solving coupled optimization problems in a distributed way given restrictions on the communication topology. The iterative pro...
Björn Johansson, Tamás Keviczky, Mikae...
AUTOMATICA
2008
127views more  AUTOMATICA 2008»
14 years 10 months ago
On decentralized negotiation of optimal consensus
A consensus problem consists of finding a distributed control strategy that brings the state or output of a group of agents to a common value, a consensus point. In this paper, we...
Björn Johansson, Alberto Speranzon, Mikael Jo...
AAAI
2010
14 years 11 months ago
Interactive Learning Using Manifold Geometry
We present an interactive learning method that enables a user to iteratively refine a regression model. The user examines the output of the model, visualized as the vertical axis ...
Eric Eaton, Gary Holness, Daniel McFarlane