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AAAI 2004

Repeated Observation Models

Conference Paper Knowledge Representation and Reasoning Artificial Intelligence

Abstract

Repetition is an important phenomenon in a variety of domains, such as music, computer programs and architectural drawings. A generative model for these domains should account for the possibility of repetition. We present repeated observation models (ROMs), a framework for modeling sequences that explicitly allows for repetition. In a ROM, an element is either generated by copying a previous element, or by using a base model. We show how to build ROMs using ngrams and hidden Markov models as the base model. We also describe an extension of ROMs in which entire subsequences are repeated together. Results from a music modeling domain show that ROMs can lead to dramatic improvement in predictive ability.

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Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
742728365906509715
v2026.09.13