Abstract. The development of robots that learn from experience is a relentless challenge confronting artificial intelligence today. This paper describes a robot learning method whi...
With the rapid growth of real application domains for NLP systems, there is a genuine demand for a general toolkit from which programmers with no linguistic knowledge can build sp...
Hassan Alam, Hua Cheng, Rachmat Hartono, Aman Kuma...
Multiply sectioned Bayesian networks (MSBNs) provide a coherent and flexible formalism for representing uncertain knowledge in large domains. Global consistency among subnets in a...
The ability to handle changes is a characteristic feature of successful software projects. The problem addressed in this paper is what should be done in project planning and itera...
We demonstrate the advantages of using Bayesian multi layer perceptron (MLP) neural networks for image analysis. The Bayesian approach provides consistent way to do inference by c...