Jeremy Ludwig

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This paper describes a number of extensions to the dynamic scripting reinforcement learning algorithm which was designed for modern computer games. These enhancements include integration with an AI tool and automatic state construction. A subset of a real-time strategy game is used to demonstrate the learning algorithm both improving the performance of(More)
Dynamic scripting is a reinforcement learning algorithm designed specifically to learn appropriate tactics for an agent in a modern computer game, such as Neverwinter Nights. This reinforcement learning algorithm has previously been extended to support the automatic construction of new abstract states to improve its context sensitivity and integrated with a(More)
Whenever an auto manufacturer refreshes an existing car or truck model or builds a new one, the model will undergo hundreds if not thousands of tests before the factory line and tooling is finished and vehicle production beings. These tests are generally carried out on expensive, custom-made vehicles because the new factory lines for the model do not exist(More)
This paper provides an overview of the area of psychological inspired symbolic cognitive architectures. It does this by first defining the terms that describe this research area and by selecting three architectures to examine: ACT-R, EPIC, and Soar. For each of these architectures, the motivations, assumptions, and features are evaluated. The similarities(More)
In order for simulation based training to help prepare soldiers for modern asymmetric tactics, opponent models of behavior must become more dynamic and challenge trainees with adaptive threats consistent with those encountered increasingly in the real world. In this presentation we describe an adaptive behavior modeling framework designed to represent(More)
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