|Title||Case-Based Plan Recognition Using Action Sequence Graphs|
|Publication Type||Conference Proceedings|
|Year of Conference||2014|
|Authors||Vattam, S, Aha, DW, Floyd, MW|
|Conference Name||Proceedings of the Twenty-Second International Conference on Case-Based Reasoning|
|Conference Location||Cork, Ireland|
We present SET-PR, a novel case-based plan recognition algorithm that is tolerant to missing and misclassified actions in its input action sequences. SET-PR uses a novel representation called action sequence graphs to represent stored plans in its plan library and a similarity metric that uses a combination of graph degree sequences and object similarity to retrieve relevant plans from its library. We evaluated SET-PR by measuring plan recognition convergence and precision with increasing levels of missing and misclassified actions in its input. In our experiments, SET-PR tolerated 20%-30% of input errors without compromising plan recognition performance.
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