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» Combining Learned Discrete and Continuous Action Models
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NIPS
2004
15 years 8 months ago
Multiple Alignment of Continuous Time Series
Multiple realizations of continuous-valued time series from a stochastic process often contain systematic variations in rate and amplitude. To leverage the information contained i...
Jennifer Listgarten, Radford M. Neal, Sam T. Rowei...
SARA
2009
Springer
16 years 1 months ago
Some Interval Approximation Techniques for MINLP
MINLP problems are hard constrained optimization problems, with nonlinear constraints and mixed discrete continuous variables. They can be solved using a Branch-and-Bound scheme c...
Nicolas Berger, Laurent Granvilliers
IJHIS
2006
94views more  IJHIS 2006»
15 years 6 months ago
A new fine-grained evolutionary algorithm based on cellular learning automata
In this paper, a new evolutionary computing model, called CLA-EC, is proposed. This model is a combination of a model called cellular learning automata (CLA) and the evolutionary ...
Reza Rastegar, Mohammad Reza Meybodi, Arash Hariri
IJCAI
2007
15 years 8 months ago
Analogical Learning in a Turn-Based Strategy Game
A key problem in playing strategy games is learning how to allocate resources effectively. This can be a difficult task for machine learning when the connections between actions a...
Thomas R. Hinrichs, Kenneth D. Forbus
AI
1998
Springer
15 years 10 months ago
Sequential Instance-Based Learning
This paper presents and evaluates sequential instance-based learning (SIBL), an approach to action selection based upon data gleaned from prior problem solving experiences. SIBL le...
Susan L. Epstein, Jenngang Shih