Author: Karen Myers
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Learning Procedures by Augmenting Sequential Pattern Mining with Planning Knowledge
This paper explores the use of filtering heuristics based on action models for automated planning to augment sequence mining techniques.
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Bridging the Gap: Converting Human Advice into Imagined Examples
We present an approach that converts human advice into synthetic or imagined training experiences, serving to scaffold the low-level representations of simple, reactive learning systems such as reinforcement learners.
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Privacy-Aware Adaptive Scheduling for Coalition Operations
We consider the use of an advanced cryptographic technique called secure multi-party computation to enable coalition members to achieve joint objectives while still meeting privacy requirements.
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Explanation to Avert Surprise
We present an explanation framework based on the notion of explanation drivers —i.e., the intent or purpose behind agent explanations. We focus on explanations meant to reconcile expectation violations and enumerate a set of triggers for proactive explanation.
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Semantic Instrumentation of Virtual Environments for Training
We discuss an approach in which the virtual environment is semantically instrumented in order to allow for the tracking of and reasoning about open-ended learner activity therein.
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Demonstration-based Solution Authoring for Skill Assessment
This paper reports on an approach to creating solution models for automated skill assessment using an example-based methodology, specifically targeting domains for which solution models must support robustness to learner mistakes.
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Approximate Graph Matching for Mistake-tolerant Skill Assessment
This paper presents an approach to automated assessment for online training based on approximate graph matching.
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Assessment and Content Authoring in Semantic Virtual Environments
This paper presents an approach to training in VEs that directly addresses these challenges and summarizes its application to a weapons maintenance task.
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Solution Authoring via Demonstration and Annotation: An Empirical Study
This paper reports on a concept validation study that provides an empirical basis for the design of solution authoring frameworks based on end-user programming techniques.
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Evaluating Multimedia Features and Fusion for Example-Based Event Detection
To study the value of multimedia features and fusion for representing and learning events from a set of example video clips, we created SESAME, a system for video SEarch with Speed and Accuracy for Multimedia Events.
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Drill Evaluation for Training Procedural Skills
This paper describes an automated assessment and feedback capability that has been applied to training for a complex software system in widespread use throughout the U.S. Army.
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Learning by Demonstration for a Collaborative Planning Environment
We describe the deployment of a learning by demonstration capability to support user creation of automated procedures in a collaborative planning environment that is used widely by the U.S. Army.