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Negative Human Rights as a Basis for Long-Term AI Safety and Regulation (Abstract Reprint)

Ondrej Bajgar, Jan Horenovsky
IJCAI 2024 pp. 8474
doi:10.24963/ijcai.2024/946 /ijcai/2024/bajgar2024ijcai-negative/

Abstract

We consider the problem of quickly providing strong lower bounds for the planar Euclidean shortest path (ESP) problem. Such lower bounds are crucial for guiding the search in A* type approaches or for proving quality guarantees for algorithms that compute approximate solutions. Our contributions are two-fold: we show how to simplify ESP instances such that computing and storing a visibility graph becomes feasible while distances within the simplified instance are guaranteed to constitute lower bounds for the original problem instance. Furthermore we show how to precompute a space efficient data structure that allows to perform distance queries on visibility graphs within few microseconds with negligible space overhead.

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Text

Bajgar and Horenovsky. "Negative Human Rights as a Basis for Long-Term AI Safety and Regulation (Abstract Reprint)." International Joint Conference on Artificial Intelligence, 2024. doi:10.24963/ijcai.2024/946

Markdown

[Bajgar and Horenovsky. "Negative Human Rights as a Basis for Long-Term AI Safety and Regulation (Abstract Reprint)." International Joint Conference on Artificial Intelligence, 2024.](https://mlanthology.org/ijcai/2024/bajgar2024ijcai-negative/) doi:10.24963/ijcai.2024/946

BibTeX

@inproceedings{bajgar2024ijcai-negative,
  title     = {{Negative Human Rights as a Basis for Long-Term AI Safety and Regulation (Abstract Reprint)}},
  author    = {Bajgar, Ondrej and Horenovsky, Jan},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2024},
  pages     = {8474},
  doi       = {10.24963/ijcai.2024/946},
  url       = {https://mlanthology.org/ijcai/2024/bajgar2024ijcai-negative/}
}