2021
IJCAI
IJCAI 2021
What’s the Context? Implicit and Explicit Assumptions in Model-Based Goal Recognition
Abstract
Every model involves assumptions. While some are standard to all models that simulate intelligent decision-making (e.g., discrete/continuous, static/dynamic), goal recognition is well known also to involve choices about the observed agent: is it aware of being observed? cooperative or adversarial? In this paper, we examine not only these but the many other assumptions made in the context of model-based goal recognition. By exploring their meaning, the relationships between them and the confusions that can arise, we demonstrate their importance, shed light on the way trends emerge in AI, and suggest a novel means for researchers to uncover suitable avenues for future work.
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The Questioner
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Keyword Pioneer
— assumption analysis
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Deep Learning, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning