Construction and Adaptation of AI Behaviors in Computer Games

Computer games are an increasingly popular application for Artificial Intelligence (AI) research, and conversely AI is an increasingly popular selling point for commercial digital games. AI for non playing characters (NPC) in computer games tends to come from people with computing skills well beyond the average user. The prime reason behind the lack of involvement [...]

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Real-Time Case-Based Reasoning for Interactive Digital Entertainment

(Click image to view the video – it’s near the bottom of the new page.) User-generated content is everywhere: photos, videos, news, blogs, art, music, and every other type of digital media on the Social Web. Games are no exception. From strategy games to immersive virtual worlds, game players are increasingly engaged in creating and sharing [...]

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User-Generated AI for Interactive Digital Entertainment

User-generated content is everywhere: photos, videos, news, blogs, art, music, and every other type of digital media on the Social Web. Games are no exception. From strategy games to immersive virtual worlds, game players are increasingly engaged in creating and sharing nearly all aspects of the gaming experience: maps, quests, artifacts, avatars, clothing, even games [...]

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Drama Management and Player Modeling for Interactive Fiction Games

A growing research community is working towards employing drama management components in story-based games. These components gently guide the story towards a narrative arc that improves the player’s gaming experience. In this paper we evaluate a novel drama management approach deployed in an interactive fiction game called Anchorhead. This approach uses player’s feedback as the [...]

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An Ensemble Learning and Problem Solving Architecture for Airspace Management

In this paper we describe the application of a novel learning and problem solving architecture to the domain of airspace management, where multiple requests for the use of airspace need to be reconciled and managed automatically. The key feature of our “Generalized Integrated Learning Architecture” (GILA) is a set of integrated learning and reasoning (ILR) [...]

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Goal-Driven Learning in the GILA Integrated Intelligence Architecture

Goal Driven Learning (GDL) focuses on systems that determine by themselves what has to be learned and how to learn it. Typically GDL systems use meta-reasoning capabilities over a base reasoner, identifying learning goals and devising strategies. In this paper we present a novel GDL technique to deal with complex AI systems where the meta-reasoning [...]

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Argumentation-Based Information Exchange in Prediction Markets

We investigate how argumentation processes among a group of agents may affect the outcome of group judgments. In particular we focus on prediction markets (also called information markets). We investigate how the existence of social networks (that allow agents to argue with one another to improve their individual predictions) effect on group judgments. Social networks [...]

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Case-Based Reasoning for Gas Turbine Diagnostics

General Electric used case-based reasoning for gas turbine diagnostics at their monitoring and diagnostics center in Atlanta, GA. This application had requirements that included accuracy, maintainability, modularity, parameterization, robustness, and integration of the system into an existing infrastructure. The CBR system has a modular “plug and play” architecture to facilitate experimentation and optimization. It was [...]

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Plan Recognition in Large-Scale Multi-Agent Tactical Domains

This research addresses the task of representing and recognizing events in a tactical domain from large-scale spatio-temporal data under conditions of limited observability and high noise with real-time response constraints.  These assumptions differ from those traditionally made in  plan recognition and produce a problem that combines aspects of plan recognition, pattern recognition and object tracking. [...]

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IRIA: The Information Research Intelligent Assistant

The explosion of information in the modern environment demands the ability to collect, organize, manage, and search large amounts of information across a wide variety of real-world applications. The primary tools available for such tasks are large-scale database systems and keyword-based document search techniques. However, such tools are rapidly proving inadequate: traditional database systems do [...]

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