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» Learning Rules for Adaptive Planning
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VL
2010
IEEE
160views Visual Languages» more  VL 2010»
13 years 7 months ago
Toward End-User Debugging of Machine-Learned Classifiers
Many machine-learning algorithms learn rules of behavior from individual end users, such as taskoriented desktop organizers and handwriting recognizers. These rules form a generat...
Todd Kulesza
CA
1999
IEEE
14 years 1 months ago
Fast Synthetic Vision, Memory, and Learning Models for Virtual Humans
This paper presents a simple and efficient method of modeling synthetic vision, memory, and learning for autonomous animated characters in real-time virtual environments. The mode...
James J. Kuffner Jr., Jean-Claude Latombe
GECCO
2009
Springer
150views Optimization» more  GECCO 2009»
14 years 3 months ago
Discrete dynamical genetic programming in XCS
A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks. This paper presents results fr...
Richard Preen, Larry Bull
FLAIRS
2006
13 years 10 months ago
Robot Navigation Using Integrated Retrieval of Behaviors and Routes
RUPART1 is a hybrid robot control system for navigating a real-world, academic building. Hybrid robot control systems provide robust low-level navigation together with strategic p...
Susan Eileen Fox, Peter Anderson-Sprecher
OTM
2005
Springer
14 years 2 months ago
OWL-Based User Preference and Behavior Routine Ontology for Ubiquitous System
In ubiquitous computing, behavior routine learning is the process of mining the context-aware data to find interesting rules on the user’s behavior, while preference learning tri...
Kim Anh Pham Ngoc, Young-Koo Lee, Sungyoung Lee