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» Evolving Artificial Neural Networks that Develop in Time
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AIME
2001
Springer
15 years 4 months ago
NasoNet, Joining Bayesian Networks and Time to Model Nasopharyngeal Cancer Spread
Abstract. Cancer spread is a non-deterministic dynamic process. As a consequence, the design of an assistant system for the diagnosis and prognosis of the extent of a cancer should...
Severino F. Galán, Francisco Aguado, Franci...
ML
2000
ACM
157views Machine Learning» more  ML 2000»
14 years 11 months ago
A Multistrategy Approach to Classifier Learning from Time Series
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
William H. Hsu, Sylvian R. Ray, David C. Wilkins
CIG
2006
IEEE
15 years 5 months ago
Modeling Children's Entertainment in the Playware Playground
Abstract— This paper introduces quantitative measurements/metrics of qualitative entertainment features within interactive playgrounds inspired by computer games and proposes art...
Georgios N. Yannakakis, Henrik Hautop Lund, John H...
SIGCOMM
2009
ACM
15 years 6 months ago
A virtual platform for network experimentation
Although the diversity of platforms for network experimentation is a boon to the development of protocols and distributed systems, it is challenging to exploit its benefits. Impl...
Olaf Landsiedel, Georg Kunz, Stefan Götz, Kla...
AUSAI
2004
Springer
15 years 5 months ago
A Comparison of BDI Based Real-Time Reasoning and HTN Based Planning
The Belief-Desire-Intention (BDI) model of agency is an architecture based on Bratman’s theory of practical reasoning. Hierarchical Task Network (HTN) decomposition on the other ...
Lavindra de Silva, Lin Padgham