This paper discusses the empirical evaluation of improving generalization performance of neural networks by systematic treatment of training and test failures. As a result of syst...
This paper presents a logistic algorithm that improves traffic conditions in a network-like automated material handling system (AMHS). The algorithm uses a lookahead procedure and...
Anytime algorithms offer a tradeoff between solution quality and computation time that has proved useful in applying artificial intelligence techniques to time-critical problems. ...
Anytime algorithms, whose quality of results improves gradually as computation time increases, provide useful performance components for timecritical planning and control of robot...
In this paper, we introduce a domain-independent classification framework based on both k-nearest neighbor and Naïve Bayesian classification algorithms. The architecture of our s...