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Master's Dissertation
DOI
https://doi.org/10.11606/D.45.2006.tde-15022010-161012
Document
Author
Full name
Felipe Werndl Trevizan
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2006
Supervisor
Committee
Barros, Leliane Nunes (President)
Cozman, Fabio Gagliardi
Hashimoto, Ronaldo Fumio
Title in Portuguese
Um modelo unificado para planejamento sob incerteza
Keywords in Portuguese
MDP
MDPST
Planejamento Probabilístico
Abstract in Portuguese
Dois modelos principais de planejamento em inteligência artificial são os usados, respectivamente, em planejamento probabilístico (MDPs e suas generalizações) e em planejamento não-determinístico (baseado em model checking). Nessa dissertação será: (1) exibido que planejamento probabilístico e não-determinístico são extremos de um rico contínuo de problemas capaz de lidar simultaneamente com risco e incerteza (Knightiana); (2) obtido um modelo para unificar esses dois tipos de problemas usando MDPs imprecisos; (3) derivado uma versão simplificada do princípio ótimo de Bellman para esse novo modelo; (4) exibido como adaptar e analisar algoritmos do estado-da-arte, como (L)RTDP e LDFS, nesse modelo unificado. Também será discutido exemplos e relações entre modelos já propostos para planejamento sob incerteza e o modelo proposto.
Title in English
An unified model for planning under uncertainty
Keywords in English
MDP
MDPST
Probabilistic Planning
Abstract in English
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 dissertation 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.
 
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dissertacao.pdf (795.10 Kbytes)
Publishing Date
2011-05-26
 
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