184 search results - page 19 / 37 » Learning Within the BDI Framework: An Empirical Analysis |
ICCV
2007
IEEE
14 years 9 months ago
2007
IEEE
Most existing subspace analysis-based tracking algorithms utilize a flattened vector to represent a target, resulting in a high dimensional data learning problem. Recently, subspa...
GECCO
2005
Springer
14 years 1 months ago
2005
Springer
Code bloat, the excessive increase of code size, is an important issue in Genetic Programming (GP). This paper proposes a theoretical analysis of code bloat in the framework of sy...
AAAI
2008
13 years 10 months ago
2008
We introduce the problem of zero-data learning, where a model must generalize to classes or tasks for which no training data are available and only a description of the classes or...
AI
2002
Springer
13 years 7 months ago
2002
Springer
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
HICSS
2003
IEEE
14 years 1 months ago
2003
IEEE
Our “information-oriented” society shows an increasing exigency of life-long learning. In such framework, online Learning is becoming an important tool to allow the flexibilit...