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SOFSEM
2007
Springer
14 years 4 months ago
Incremental Learning of Planning Operators in Stochastic Domains
In this work we assume that there is an agent in an unknown environment (domain). This agent has some predefined actions and it can perceive its current state in the environment c...
Javad Safaei, Gholamreza Ghassem-Sani
SYNASC
2005
IEEE
97views Algorithms» more  SYNASC 2005»
14 years 3 months ago
A Reinforcement Learning Algorithm for Spiking Neural Networks
The paper presents a new reinforcement learning mechanism for spiking neural networks. The algorithm is derived for networks of stochastic integrate-and-fire neurons, but it can ...
Razvan V. Florian
AUSAI
2004
Springer
14 years 3 months ago
A Bayesian Metric for Evaluating Machine Learning Algorithms
How to assess the performance of machine learning algorithms is a problem of increasing interest and urgency as the data mining application of myriad algorithms grows. The standard...
Lucas R. Hope, Kevin B. Korb
GLOBECOM
2008
IEEE
13 years 10 months ago
Autonomous Network Management Using Cooperative Learning for Network-Wide Load Balancing in Heterogeneous Networks
Traditional hop-by-hop dynamic routing makes inefficient use of network resources as it forwards packets along already congested shortest paths while uncongested longer paths may b...
Minsoo Lee, Xiaohui Ye, Dan Marconett, Samuel John...
AI
1999
Springer
13 years 9 months ago
Learning by Discovering Concept Hierarchies
We present a new machine learning method that, given a set of training examples, induces a definition of the target concept in terms of a hierarchy of intermediate concepts and th...
Blaz Zupan, Marko Bohanec, Janez Demsar, Ivan Brat...