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1 Architecture The University of Texas at Austin's entry in the CEC 2011 Human-like Bots Competition is UT^2, which stand for University of Texas in Unreal Tournament. The UT^2 bot uses a behavior-based architecture in which a list of behavior modules is cycled through in priority order on every logic cycle. Each behavior module has a trigger, and if a(More)
"Plain question and plain answer make the shortest road out of most perplexities." Mark Twain-Life on the Mississippi. A new methodology for the measurement of the neural substrates of human social interaction is described. This technology, termed "Hyperscan," embodies both the hardware and the software necessary to link magnetic resonance scanners through(More)
A major goal for AI is to allow users to interact with agents that learn in real time, making new kinds of interactive simulations, training applications, and digital entertainment possible. This paper describes such a learning technology, called real-time NeuroEvolution of Augmenting Topologies (rtNEAT), and describes how rtNEAT was used to build the(More)
Video games provide an opportunity and challenge for the soft computational intelligence methods like the symbolic games did for " good old-fashioned artificial intelligence. " This article reviews the achievements and future prospects of one particular approach, that of evolving neural networks, or neuroevolution. This approach can be used to construct(More)
—The UTˆ2 bot, which had a humanness rating of 27.2727% in BotPrize 2010, is based on two core ideas: (1) multiobjective neuroevolution is used to learn skilled combat behavior, but filters on the available combat actions ensure that the behavior is still human-like despite being evolved for performance, and (2) a database of traces of human play is used to(More)
— The General Game Playing Competition [1] poses a unique challenge for Artificial Intelligence. To be successful, a player must learn to play well in a limited number of example games encoded in first-order logic and then generalize its game play to previously unseen games with entirely different rules. Because good opponents are usually not available,(More)
Video and computer games provide a rich platform for testing adaptive decision systems such as value-based reinforcement learning and neuroevolution. However, integrating such systems into the game environment and evaluating their performance in it is time and labor intensive. In this paper, an approach is developed for using general integration and(More)
Imitation is a powerful and pervasive primitive underlying examples of intelligent behavior in nature. Can we use it as a tool to help build artificial agents that behave like humans do? This question is studied in the context of the BotPrize competition, a Turing-like test where computer game bots compete by attempting to fool human judges into thinking(More)
Neuroevolution is a promising approach for constructing intelligent agents in many complex tasks such as games, robotics, and decision making. It is also well suited for evolving team behavior for many multiagent tasks. However, new challenges and opportunities emerge in such tasks, including facilitating cooperation through reward sharing and(More)
OpenNERO is an open source game platform designed for game AI research. The software package combines features commonly available in modern game engines (such as 3D graphics, physics simulation, 3D audio rendering , networked play, and a powerful scripting interface) with an easy to use API and tools for defining machine learning tasks, environments, and(More)