Usability evaluation is an increasingly important part of the user interface design process. However, usability evaluation can be expensive in terms of time and human resources, and automation is therefore a promising way to augment existing approaches. This article presents an extensive survey of usability evaluation methods, organized according to a new taxonomy that emphasizes the role of automation. The survey analyzes existing techniques, identifies which aspects of usability evaluation automation are likely to be of use in future research, and suggests new ways to expand existing approaches to better support usability evaluation. Categories and Subject Descriptors: H.1.2 [Information Systems]: User/Machine Systems—human factors; human information processing; H.5.2 [Information Systems]: User Interfaces—benchmarking; evaluation/methodology; graphical user

This paper presents a computational model of real-time task-oriented dialogue skills. The architecture, termed Ymir, bridges between multimodal perception and multimodal action and supports the creation of autonomous computer characters that afford full-duplex, real-time face-to-face interaction with a human. Ymir has been prototyped in software, and a humanoid created, called Gandalf, capable of fluid multimodal dialogue. Ymir demonstrates several new ideas in the creation of communicative computer agents, including perceptual integration of multimodal events, distributed planning and decision making, an explicit handling of real-time, and layered input analysis and motor control with human characteristics. This paper describes the architecture and explains its main elements. Examples ofimplementation and performance are given, and the architectures limitations and possibilities are discussed.

Abstract. One approach in pursuit of general intelligent agents has been to concentrate on the underlying cognitive architecture, of which Soar is a prime

This thesis describes EM-ONE, an architecture for commonsense thinking capable of reflective reasoning about situations involving physical, social, and mental dimensions. EM-ONE uses as its knowledge base a library of commonsense narratives, each describing the physical, social, and mental activity that occurs during an interaction between several actors. EM-ONE reasons with these narratives by applying "mental critics, " procedures that debug problems that exist in the outside world or within EM-ONE itself. Mental critics draw upon commonsense narratives to suggest courses of action, methods for deliberating about the circumstances and consequences of those actions, and—when things go wrong—ways to reflect upon and debug the activity of previously invoked mental critics. Mental critics are arranged into six layers, the reactive, deliberative, reflective, self-reflective, self-conscious, and self-ideals layers. The selection of mental critics within these six layers is itself guided by a separate collection

Abstract. This chapter addresses the problem of producing and maintaining progress in agent design. New architectures often hold important insights into the problems of designing intelligence. Unfortunately, these ideas can be difficult to harness, because on established projects switching between architectures and languages carries high cost. We propose a solution whereby the research community takes responsibility for re-expressing innovations as idioms or extensions of one or more standard architectures. We describe the process and provide an example — the concept of a Basic Reactive Plan. This idiom occurs in several influential agent architectures, yet in others is difficult to express. We also discuss our proposal’s relation to the the roles of architectures, methodologies and toolkits in the design of agents. 1

Select-a-Kibitzer is a computerized tool that gives feedback to students on their compositions in a unique way. The project is based on composition research which describes the process of writing as one of simultaneously solving multiple, possibly conflicting constraints. In Select-a-Kibitzer, each constraint is personified by a di#erent character. A student enters a composition into the tool and then asks for feedback. A variety of natural language processing techniques are used to analyze the text. Then, each of the characters gives feedback on the text from its particular point of view. The student can focus on particular aspects of the writing process by choosing to get feedback from only one or a small subset of the critics. Select-a-Kibitzer differs greatly from standard "style checker" mechanisms that focus on surface features of the text. By using Latent Semantic Analysis, Select-a-Kibitzer can address a wide-range of meaning-oriented composition issues, including co...

Abstract. This volume is intended to help advance the field of artificial neural networks along the lines of complexity present in animal brains. In particular, we are interested in examining the biological phenomena of modularity and specialized learning. These topics are already the subject of research in another area of artificial intelligence. The design of complete autonomous agents (CAA), such as mobile robots or virtual reality characters, has been dominated by modular architectures and context-driven action selection and learning. In this chapter, we help bridge the gap from neuroscience to artificial neural networks (ANN) by incorporating CAA. We do this both directly, by using CAA as a metaphor to consider requirements for ANN, and indirectly, by using CAA research to better understand and model neuroscience. We discuss the strengths and the limitations of these forms of modeling, and propose as future work extensions to CAA inspired by neuroscience.

One of the defining features of intelligent behaviour is the ordering of individual expressed actions into coherent, apparently rational patterns. Psychology has long assumed that hierarchical and sequential structures internal to the intelligent agent underlie this expression. Recently these assumptions have been challenged by claims that behaviour controlled by such structures is necessarily rigid, brittle, and incapable of reacting quickly and opportunistically to changes in the environment (Hendriks-Jansen 1996, Goldfield 1995, Brooks 1991a). This dissertation is intended to support the hypothesis that sequential and hierarchical structures are necessary to intelligent behaviour, and to refute the above claims of their impracticality. Three forms of supporting evidence are provided: • a demonstration in the form of experimental results in two domains that structured intelligence can lead to robust and reactive behaviour, • a review of recent research results and paradigmatic trends within artificial intelligence, and • a similar examination of related research in natural intelligence.

This proposal was originally a short paper relating representations of intelligence between three fields: psychology, neuroscience and artificial intelligence (AI). I particularly emphasize the role of modularity in these three areas. To my knowledge, this paper was never published — it was written on commission, but several years ago and I have just done yet another web search to find it. Further,

This article examines Marvin Minsky's Society of Mind theory of human cognition. We describe some of the history behind the theory, review several of the specific mechanisms and representations that Minsky proposes, and consider related developments in Artificial Intelligence since the theory's publication.