ML Anthology

Planning Under Risk and Knightian Uncertainty

Felipe W. Trevizan, Fábio Gagliardi Cozman, Leliane Nunes de Barros
IJCAI 2007 pp. 2023-2028
/ijcai/2007/trevizan2007ijcai-planning/

Abstract

Two noteworthy models of planning in AI are probabilistic planning (based on MDPs and its generalizations) and nondeterministic planning (mainly based on model checking). In this paper we: (1) show that probabilistic and nondeterministic planning are extremes of a rich continuum of problems that deal simultaneously with risk and (Knightian) uncertainty; (2) obtain a unifying model for these problems using imprecise MDPs; (3) derive a simplified Bellman's principle of optimality for our model; and (4) show how to adapt and analyze state-of-art algorithms such as (L)RTDP and LDFS in this unifying setup. We discuss examples and connections to various proposals for planning under (general) uncertainty. URL: http://www.ime.usp.br/~trevisan/papers/ijcai-07.pdf

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Text

Trevizan et al. "Planning Under Risk and Knightian Uncertainty." International Joint Conference on Artificial Intelligence, 2007.

Markdown

[Trevizan et al. "Planning Under Risk and Knightian Uncertainty." International Joint Conference on Artificial Intelligence, 2007.](https://mlanthology.org/ijcai/2007/trevizan2007ijcai-planning/)

BibTeX

@inproceedings{trevizan2007ijcai-planning,
  title     = {{Planning Under Risk and Knightian Uncertainty}},
  author    = {Trevizan, Felipe W. and Cozman, Fábio Gagliardi and de Barros, Leliane Nunes},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2007},
  pages     = {2023-2028},
  url       = {https://mlanthology.org/ijcai/2007/trevizan2007ijcai-planning/}
}