Annotations

Notice! For all terminology questions, please refer to the Lingo page, please. Though the following has mostly, nay all links in it's composition, this is not how it shall remain. Please keep that in mind when being judgmental of the below page.

[|An Introduction to Software Agents] Jeffrey M. Bradshaw This introductory paper to the world of Software agents is a great read if one has any interest in the subject at all. It provides a wonderful insight into the definition, design, and nature of Software Agents of all sorts, even having a brief segment on the history of the Artificially Intelligent being as a preface. Many insights are outlined on the different varieties of Agents there are, from Distributive in structure to a more stagnant variety that focuses more on action than deliberation. This will most definitely be a source I will defer to for advice on the construction of my project not only because of the sheer amount of information provided but for the staggering amount of reference material I can pick up from the bibliography at the bottom of the pdf.

[|Fuzzy Logic Programming and Fuzzy Control]  Giangiacomo Gerla Studia Logica: An International Journal for Symbolic Logic Vol. 79, No. 2 (Mar., 2005), pp. 231-254 This Article is my go to source for fuzzy logic programming methods. It outlines how fuzzy logic can be used to provide and maintain software efficiency via certain methods, of which exquisitely detailed examples are provided. I admit, this material is very complex and I have been struggling quite a bit to keep up with it, I've got the gist of it and am working around the clock to decipher more to take away from the article.

[|Data Mining and Serial Documents] Rachid Anane Computers and the Humanities Vol. 35, No. 3 (Aug., 2001), pp. 299-314 Data mining is a very relevant area of study for my project because of the methods used. I knew that if I could grasp the concepts and the methods by which existing programs can 'mine' information fields for data by associative pattern construction and recognition, I could apply it to a program that specializes in natural language processing for improved sentence pattern recognition. While the article mainly focuses on Data mining programs as they pertain to Data Warehouses, servers which document permanent data such as historical records, the same kinds of processes can be applied to any kind of pattern development.

[|An Introduction to Neural Networks and a Comparison with Artificial Intelligence and Expert Systems]  Fatemeh Zahedi Interfaces Vol. 21, No. 2 (Mar. - Apr., 1991), pp. 25-38 This article is important in that it implies that two different methods at simulating intelligence artificially, Neural Networking and Expert systems, can work together to make a stronger Artificial Intelligence. The former tries to simulate the human mind by running the same base input through unique yet parallel processes to try and elicit a natural response. This allows for different tests to be run on the same base input, therefore checking the data for consistency. The latter tries to approach problems as an expert would in the given field, processing data sequentially to try and come up with one large answer. They both have potential, and they both have shortcomings. I would not have considered using the two methods together were it not for this article, they just seemed so distant from one another.

[|"Machine Learning Lecture 1" (CS 229)] Ng, Andrew Stanford, California, US Huang Auditorium This introductory lecture from Stanford University covers many of the basic aspects of Machine Learning, the main category into which data mining, supervised or unsupervised learning methods, speech recognition, and different varieties of data processing are elaborated upon in brief. This lecture was and continues to be a great source for finding out what kinds of sources I need to look for and what kinds of subjects I need to look into and research.