This paper presents an anytime algorithm for incremental intention recognition in a changing world. The algorithm is performed by dynamically constructing the intention recognition model on top of a prior domain knowledge base. The model is occasionally reconfigured by situating itself in the changing world and removing newly found out irrelevant intentions. We also discuss some approaches to knowledge base representation for supporting situation-dependent model construction. Reconfigurable Bayesian Networks are employed to produce the intention recognition model.
|Title of host publication||AAAI Fall Symposium Series|
|Place of Publication||http://www.aaai.org/home.html|
|Publication status||Published - 1 Jan 2010|
|Event||AAAI Fall Symposium Series - |
Duration: 1 Jan 2010 → …
|Conference||AAAI Fall Symposium Series|
|Period||1/01/10 → …|
DI Group Author (2010). Anytime Intention Recognition via Incremental Bayesian Network Reconstruction. In AAAI (Ed.), AAAI Fall Symposium Series (Vol. http://www.aaai.org/ocs/index.php/FSS/FSS10/schedConf/presentati, pp. 20-25). http://www.aaai.org/home.html: AAAI.