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GECCO
2006
Springer
168views Optimization» more  GECCO 2006»
15 years 1 months ago
A Bayesian approach to learning classifier systems in uncertain environments
In this paper we propose a Bayesian framework for XCS [9], called BXCS. Following [4], we use probability distributions to represent the uncertainty over the classifier estimates ...
Davide Aliprandi, Alex Mancastroppa, Matteo Matteu...
ECSCW
2003
14 years 11 months ago
Supporting Collaboration Ubiquitously: An Augmented Learning Environment for Architecture Students
While CSCW research has mostly been focusing on desktop applications there is a growing interest on ubiquitous and tangible computing. We present ethnographic fieldwork and prototy...
Giulio Iacucci, Ina Wagner
ICPR
2008
IEEE
15 years 10 months ago
Incremental learning in non-stationary environments with concept drift using a multiple classifier based approach
We outline an incremental learning algorithm designed for nonstationary environments where the underlying data distribution changes over time. With each dataset drawn from a new e...
Matthew T. Karnick, Michael Muhlbaier, Robi Polika...
GIS
2008
ACM
14 years 9 months ago
An ACS cooperative learning approach for route finding in natural environment
This paper introduces an ant-based colony system for the representation of a verbal route description. It is grounded on a natural metaphor that mimics the behavior of ant colonie...
David Brosset, Christophe Claramunt, Eric Saux
NEUROSCIENCE
2001
Springer
15 years 2 months ago
Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources
We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...
Doina Caragea, Adrian Silvescu, Vasant Honavar