If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
This article gives an overview of current research on animated pedagogical agents at the Center for Advanced Research in Technology for Education (CARTE) at the University of Southern California/Information Sciences Institute. Animated pedagogical agents, nicknamed guidebots, interact with learners to help keep learning activities on track. They combine the pedagogical expertise of intelligent tutoring systems with the interpersonal interaction capabilities of embodied conversational characters. They can support the acquisition of team skills as well as skills performed alone by individuals. At CARTE, we have been developing guidebots that help learners acquire a variety of problem-solving skills in virtual worlds, in multimedia environments, and on the web.
Over the past decade, we have been engaged in an extensive research effort to build virtual humans and applications that use them. Building a virtual human might be considered the quintessential AI problem, because it brings together many of the key features, such as autonomy, natural communication, and sophisticated reasoning and behavior, that distinguish AI systems. This article describes major virtual human systems we have built and important lessons we have learned along the way. Early on, we decided to focus on training human-oriented skills, such as leadership, negotiation, and cultural awareness. These skills are based on what is sometimes called tacit knowledge (Sternberg 2000), that is, knowledge that is not easily explicated or taught in a classroom setting but instead is best learned through experience.
Extempo Systems, Inc., was founded in 1995 to commercialize intelligent characters. Our team built innovative software and novel applications for several markets. We had some early-adopting customers during the Internet boom, but the company could not survive the significant downturn in corporate IT spending when the bubble burst. In 2004, Extempo ceased operations and was formally liquidated. Although our commercial venture failed, we advanced the technology for intelligent characters and learned a lot about how (not) to take them to market.
More than 40,000 learners worldwide have used TLCTS courses. TLCTS utilizes artificial intelligence technologies during the authoring process and at run time to process learner speech, engage in dialogue, and evaluate and assess learner performance. This paper describes the architecture of TLCTS and the artificial intelligence technologies that it employs and presents results from multiple evaluation studies that demonstrate the benefits of learning foreign language and culture using this approach. It includes interactive lessons that focus on particular communicative skills and interactive games that apply those skills. Heavy emphasis is placed on spoken communication: learners must learn to speak the foreign language to complete the lessons and play the games.
It uses statistical language-classification technology for mapping from a user's text input to system responses. NPCEditor provides a user-friendly editor for creating effective virtual humans quickly. It has been deployed as a part of various virtual human systems in several applications. Imagine talking to a computer system that looks and acts almost human -- it converses, understands, can rea son, and can exhibit emotion. As an example, recall such computer characters created by Hollywood moviemakers as the librarian in Time Machine, the holographic professor in I Robot, and of course, the holodeck characters in numer ous Star Trek: The Next Generation episodes.
Virtual humans are computer-generated characters designed to look and behave like real people. Studies have shown that virtual humans can mimic many of the social effects that one finds in human-human interactions such as creating rapport, and people respond to virtual humans in ways that are similar to how they respond to real people. We believe that virtual humans represent a new metaphor for interacting with computers, one in which working with a computer becomes much like interacting with a person and this can bring social elements to the interaction that are not easily supported with conventional interfaces. We present two systems that embody these ideas. The first, the twins are virtual docents in the Museum of Science, Boston, designed to engage visitors and raise their awareness and knowledge of science.
Social-emotional intelligence is an essential part of being a competent human and is thus required for humanlevel AI. When considering alternatives to the Turing test it is therefore a capacity that is important to test. We characterize this capacity as affective theory of mind and describe some unique challenges associated with its interpretive or generative nature. Mindful of these challenges we describe a five-step method along with preliminary investigations into its application. We also describe certain characteristics of the approach such as its incremental nature, and countermeasures that make it difficult to game or cheat.
The goal of an interactive narrative system is to immerse users in a virtual world such that they believe that they are an integral part of an unfolding story and that their actions can significantly alter the direction or outcome of the story. In this article we review the ways in which artificial intelligence can be brought to bear on the creation of interactive narrative systems. We lay out the landscape of about 20 years of interactive narrative research and explore the successes as well as open research questions pertaining to the novel use of computational narrative intelligence in the pursuit of entertainment, education, and training. The prevalence of storytelling in human culture may be explained by the use of narrative as a cognitive tool for situated understanding (Gerrig 1993). This narrative intelligence -- the ability to organize experience into narrative form -- is central to the cognitive processes employed across a range of experiences, from entertainment to active learning.
Twenty-five years ago I had a dream, a daydream, if you will. A dream shared with many of you. I dreamed of a special kind of computer, which had eyes and ears and arms and legs, in addition to its "brain." I did not dream that this new computer friend would be a means of making money for me or my employer or a help for my country-though I loved my country then and still do, and I have no objection to making money. I did not even dream of such a worthy cause as helping the poor and handicapped of the world using this marvelous new machine.
Although one of the fundamental goals of AI is to understand and develop intelligent systems that have all the capabilities of humans, there is little active research directly pursuing this goal. We propose that AI for interactive computer games is an emerging application area in which this goal of human-level AI can successfully be pursued. Interactive computer games have increasingly complex and realistic worlds and increasingly complex and intelligent computer-controlled characters. In this article, we further motivate our proposal of using interactive computer games for AI research, review previous research on AI and games, and present the different game genres and the roles that human-level AI could play within these genres. We then describe the research issues and AI techniques that are relevant to each of these roles.