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Learning Companion Behaviors Using Reinforcement Learning in Games

This work used Reinforcement Learning to enable NPC companions to develop preferences for actions and implemented the technique in BioWare Corp.
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Knowledge assessment: game for assessment of symptoms of child physical abuse

This paper proposes a general framework for creating an assessment game and shows how Knowledge Assessment can be used to guide the focus of subsequent training modules.
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Developing a virtual reality game for manufacturing education

The development of a virtual reality (VR) simulation game for educating engineering students in manufacturing and a player modeling technique is proposed to deliver an experience adapted for each student.
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An Automated Technique for Drafting Territories in the Board Game Risk

This work presents a technique for drafting territories in Risk that combines the Monte Carlo tree search algorithm UCT with an automated evaluation function that scores outcomes of drafts in order to shorten the length of a UCT simulation.
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Virtual character behavior architecture using cyclic scheduling

This research proposes a new Tiered Behavior Architecture model for controlling the behaviors of virtual characters and describes experiments and user studies that validate this model.
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Multiplayer Physical and Virtual Reality Games for Team-based Manufacturing Simulation

First, a hands-on activity is created that engages groups of students in the design and assembly of toy cars and a corresponding multiplayer VR game is developed, which allows for the collaboration of multiple VR users in the same virtual environment.
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Learning Character Behaviors Using Agent Modeling in Games

A new on-line reinforcement learning algorithm, ALeRT-AM, that includes an agent-modeling mechanism is introduced that is able to rapidly learn a winning strategy against other agents in a combat scenario and to adapt to changes in the environment.
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Generating Believable Virtual Characters Using Behavior Capture and Hidden Markov Models

The study showed that behavior capture is a viable alternative to existing manual scripting methods and that HMMs produced the most highly ranked variation with respect to overall believability.
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Effects of Gender on Perception and Interpretation of Video Game Character Behavior and Emotion

It is found that female gamers were more appreciative of complex behaviors than male gamers, and if game designers want players to perceive these characters in a certain way, they should consider the gender of targeted players.
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Intentional Control of Type I Error Over Unconscious Data Distortion: A Neyman–Pearson Approach to Text Classification

This article addresses the challenges in classifying textual data obtained from open online platforms, which are vulnerable to distortion and proposes the use of the Neyman–Pearson (NP) classification paradigm, which minimizes Type II error under a user-specified Type I error constraint.
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