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Tech Report kmi-97-04 Abstract


Accessing Artificial Intelligence Applications over the World-Wide Web
Techreport ID: kmi-97-04
Date: 1997
Author(s): Alberto Riva, Marco Ramoni and Clara Fassino
Web Version

In this paper we will show how LispWeb, an HTTP server entirely written in Common Lisp, can be used to access Artificial Intelligence (AI) applications over the World-Wide Web (WWW). We will discuss how an AI application can benefit from being accessible in the WWW environment, and the requirements it must satisfy in order to be usable through the WWW interaction paradigm. We will describe how a Lisp systems can be accessed through a Web-based interface, and an extension to the HTTP protocol that can be used to invoke generic functions on the LispWeb server. As an example, we will describe how an existing AI application written in Common Lisp (ERA - Epistemological Reasoning Architecture) was integrated with the LispWeb server and endowed with a graphical user interface written in Java. 1. IRCCS Policlinico San Matteo, Pavia, Italy. 2. Knowledge Media Institute, The Open University, UK. 3. Dipartimento di Informatica e Sistemistica, Università di Pavia, Italy.
 
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Social Software is...


Social Software
Social Software can be thought of as "software which extends, or derives added value from, human social behaviour - message boards, musical taste-sharing, photo-sharing, instant messaging, mailing lists, social networking."

Interacting with other people not only forms the core of human social and psychological experience, but also lies at the centre of what makes the internet such a rich, powerful and exciting collection of knowledge media. We are especially interested in what happens when such interactions take place on a very large scale -- not only because we work regularly with tens of thousands of distance learners at the Open University, but also because it is evident that being part of a crowd in real life possesses a certain 'buzz' of its own, and poses a natural challenge. Different nuances emerge in different user contexts, so we choose to investigate the contexts of work, learning and play to better understand the trade-offs involved in designing effective large-scale social software for multiple purposes.