Goal Recognition in Incomplete Domain Models

AAAI 2018 pp. 8127-8128

doi:10.1609/AAAI.V32I1.12178 /aaai/2018/pereira2018aaai-goal/

Abstract

Recent approaches to goal recognition have progressively relaxed the assumptions about the amount and correctness of domain knowledge and available observations, yielding accurate and efficient algorithms. These approaches, however, assume completeness and correctness of the domain theory against which their algorithms match observations: this is too strong for most real-world domains. In this work, we develop a goal recognition technique capable of recognizing goals using incomplete (and possibly incorrect) domain theories.

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Cite

Text

Pereira and Meneguzzi. "Goal Recognition in Incomplete Domain Models." AAAI Conference on Artificial Intelligence, 2018. doi:10.1609/AAAI.V32I1.12178

Markdown

[Pereira and Meneguzzi. "Goal Recognition in Incomplete Domain Models." AAAI Conference on Artificial Intelligence, 2018.](https://mlanthology.org/aaai/2018/pereira2018aaai-goal/) doi:10.1609/AAAI.V32I1.12178

BibTeX

@inproceedings{pereira2018aaai-goal,
  title     = {{Goal Recognition in Incomplete Domain Models}},
  author    = {Pereira, Ramon Fraga and Meneguzzi, Felipe},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2018},
  pages     = {8127-8128},
  doi       = {10.1609/AAAI.V32I1.12178},
  url       = {https://mlanthology.org/aaai/2018/pereira2018aaai-goal/}
}