Learning causation event conjunction sequences
<|reference_start|>Learning causation event conjunction sequences: This is an examination of some methods that learn causations in event sequences. A causation is defined as a conjunction of one or more cause events occurring in an arbitrary order, with possible intervening non-causal events, that lead to an effect. The methods include recurrent and non-recurrent artificial neural networks (ANNs), as well as a histogram-based algorithm. An attention recurrent ANN performed the best of the ANNs, while the histogram algorithm was significantly superior to all the ANNs.<|reference_end|>
@article{portegys2024learning,
    title={Learning causation event conjunction sequences},
    author={Thomas E. Portegys},
    journal={arXiv preprint arXiv:2402.14027},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.14027},
    primaryClass={cs.LG}
}