A Simple-Transition Model for Relational Sequences

Fern, Alan

A Simple-Transition Model for Relational Sequences

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Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence. Pages 696-700.

Abstract

We use “nearly sound” logical constraints to infer hidden states of relational processes. We introduce a simple-transition cost model, which is parameterized by weighted constraints and a statetransition cost. Inference for this model, i.e. finding a minimum-cost state sequence, reduces to a single-state minimization (SSM) problem. For relational Horn constraints, we give a practical approach to SSM based on logical reasoning and bounded search. We present a learning method that discovers relational constraints using CLAUDIEN [De Raedt and Dehaspe, 1997] and then tunes their weights using perceptron updates. Experiments in relational video interpretation show that our learned models improve on a variety of competitors.

Alan Fern. 2005. A Simple-Transition Model for Relational Sequences. In Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI-05. IJCAI, 696–700. https://ijcai.org/proceedings/2005/31

@inproceedings{ijcai2005p31,
  title     = {A Simple-Transition Model for Relational Sequences},
  author    = {Fern, Alan},
  booktitle = {Proceedings of the Nineteenth International Joint Conference on
               Artificial Intelligence, {IJCAI-05}},
  publisher = {International Joint Conferences on Artificial Intelligence},
  pages     = {696--700},
  year      = {2005},
  url       = {https://ijcai.org/proceedings/2005/31},
}

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TI  - A Simple-Transition Model for Relational Sequences
AU  - Fern, Alan
T2  - Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI-05
PB  - International Joint Conferences on Artificial Intelligence
PY  - 2005
SP  - 696
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