This paper presents an improved version of a multiagent architecture aimed at providing solutions for monitoring the interaction between the atmosphere and the ocean. The ocean sur...
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
Genetic-Based Machine Learning Systems (GBML) are comparable in accuracy with other learning methods. However, efficiency is a significant drawback. This paper presents a new rep...
My research attempts to address on-line action selection in reinforcement learning from a Bayesian perspective. The idea is to develop more effective action selection techniques b...
This paper presents a technique for learning parameterized implied constraints. They can be added to a model to improve the solving process. Experiments on implied Gcc constraints ...