Planning under Risk and Knightian Uncertainty
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 2023-2027.
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.
@inproceedings{ijcai2007p326,
title = {Planning under Risk and Knightian Uncertainty},
author = {Trevizan, Felipe W. and Cozman, Fabio Gagliardi and de Barros, Leliane Nunes},
booktitle = {Proceedings of the Twentieth International Joint Conference on
Artificial Intelligence, {IJCAI-07}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ramon López de Mántaras},
pages = {2023--2027},
year = {2007},
url = {https://ijcai.org/proceedings/2007/326},
}
TY - CPAPER TI - Planning under Risk and Knightian Uncertainty AU - Trevizan, Felipe W. AU - Cozman, Fabio Gagliardi AU - de Barros, Leliane Nunes T2 - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07 PB - International Joint Conferences on Artificial Intelligence PY - 2007 SP - 2023 EP - 2027 UR - https://ijcai.org/proceedings/2007/326 ER -Copied
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