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International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada / Software agents are application programs that perform duties in an autonomous fashion. These applications can be used to increase productivity, better use existing bandwidth, and improve present and future software application programs. By using existing established methods, and adding a layer of intelligence, software agents can add problem solving abilities to an application program.

An Instructable Software Agent (ISA) is a software agent that humans can teach through Natural Instruction Methods (NIMs)—methods humans naturally use to teach one another. Some examples of NIMs include giving demonstrations, guided practice sessions, and definitions of concepts. If software agents were instructable, humans would be able to impart knowledge to software systems though a more natural interface. In this dissertation, I address generating benchmarks for evaluating the learning ability of ISAs despite the important differences that may exist between human learners and ISAs. I first present three years of case studies uncovering the challenges of such a comparison and then make recommendations for future studies. The main contributions of this dissertation are 1. a theory of using humans to evaluate the learning ability of Instructable Software Agents (ISAs), 2. a refined method for developing curricula and benchmarks for evaluating ISAs, including a scalable lab configuration for performing human benchmarking and a suite of accompanying software tools, and 3. the case studies themselves, amounting to an in-depth ethnographic study of the issues involved in using humans to develop curricula and benchmarks for ISAs. / text

This dissertation explores the feasibility of employing software agent technology to support large-scale assessment. The research included the design, development, and evaluation of the Assessment Agent System for assessing comprehensive understanding based on concept maps. The system was designed by following an agent-oriented software design method. The Assessment Agent System is composed of five types of software agents: instructor agent, student agent, management agent, assessment agent, and reporting agent. Each of these agents was designed to possess different capabilities. Software agents in the system, through communication and cooperation, collectively provide the functionalities of user-system interaction, user management, task authoring and management, assessment delivery, task presentation, response collection, automatic assessing with feedback, and reporting. Through the process of design, development, and evaluation of the Assessment Agent System, this study demonstrates an approach that employs an agent-oriented software design method to produce sophisticated educational software applications. Furthermore, this study explored the concept map assessing method for the Assessment Agent System. When node terms and linking phrases are provided, assessing student concept maps can be automated by comparing student concept maps with assessment criteria, proposition by proposition. However, the usefulness of the proposition-comparing method depends heavily on the accuracy and thoroughness of the criterion propositions. Therefore, assessment criteria need to be continually refined and improved through examining student-created propositions. / Ph. D.

This report describes a distributed approach to social filtering based on the agent metaphor. Firstly, previous approaches are described, such as cognitive filtering and social filtering. Then a couple of previously implemented systems are presented and then a new system design is proposed. The main goal is to give the requirements and design of an agent-based system that recommends web-documents. The presented approach combines cognitive and social filtering to get the advantages from both techniques. Finally, a prototype implementation called WebCondor is described and results of testing the system are reported and discussed.

<p>Comics have been used as a programming tool for agents, giving them instructions on how to act. In this thesis I do this in reverse, I use comics to describe the actions of agents already interacting with each other to create a storytelling engine that dynamically generate stories, based on the interaction of said agents.</p><p>The model for the agent behaviours is based on the improvisational puppets model of Barbara Hayes-Roth. This model is chosen due to the nature of comics themselves. Comics like those found on newspapers and children magazines are funny because their characters behaviour depends heavily on emotions, which is why this model is well suited for this application.</p><p>This project implements an emotion-based model for agent behaviour in a way that tells a story in the form of comic strips. For this, the model is adapted to a discrete time form since the actions no longer occur in real time (like in traditional simulation games) but rather in a sequence of frames or panels. The model is inspired by the analysis of time and space mechanics in comics by Scott McCloud. The emotional model is also adapted to reflect the rather extreme emotions and responses that characterize cartoon characters.</p>

University, Diss.--Mannheim, 2006.

Universiẗat, Diss.--Erlangen-Nürnberg, 2007.

Comics have been used as a programming tool for agents, giving them instructions on how to act. In this thesis I do this in reverse, I use comics to describe the actions of agents already interacting with each other to create a storytelling engine that dynamically generate stories, based on the interaction of said agents. The model for the agent behaviours is based on the improvisational puppets model of Barbara Hayes-Roth. This model is chosen due to the nature of comics themselves. Comics like those found on newspapers and children magazines are funny because their characters behaviour depends heavily on emotions, which is why this model is well suited for this application. This project implements an emotion-based model for agent behaviour in a way that tells a story in the form of comic strips. For this, the model is adapted to a discrete time form since the actions no longer occur in real time (like in traditional simulation games) but rather in a sequence of frames or panels. The model is inspired by the analysis of time and space mechanics in comics by Scott McCloud. The emotional model is also adapted to reflect the rather extreme emotions and responses that characterize cartoon characters.

Yes / This chapter discusses a linguistically orientated model of a conversational software agent (CSA) (Panesar 2017) framework sensitive to natural language processing (NLP) concepts and the levels of adequacy of a functional linguistic theory (LT). We discuss the relationship between NLP and knowledge representation (KR), and connect this with the goals of a linguistic theory (Van Valin and LaPolla 1997), in particular Role and Reference Grammar (RRG) (Van Valin Jr 2005). We debate the advantages of RRG and consider its fitness and computational adequacy. We present a design of a computational model of the linking algorithm that utilises a speech act construction as a grammatical object (Nolan 2014a, Nolan 2014b) and the sub-model of belief, desire and intentions (BDI) (Rao and Georgeff 1995). This model has been successfully implemented in software, using the resource description framework (RDF), and we highlight some implementation issues that arose at the interface between language and knowledge representation (Panesar 2017).