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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Human-aware Contingent Planning

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Autor(es):
Andres, Ignasi [1] ; de Barros, Leliane Nunes [1, 2] ; Delgado, Karina Valdivia [3]
Número total de Autores: 3
Afiliação do(s) autor(es):
[1] Univ S ao Paulo USP, Dept Comp Sci, Inst Math & Stat, Sao Paulo - Brazil
[2] Delgado, Karina Valdivia, Univ S ao Paulo USP, Escola Artes Ciencias \& Humanidades, Sao Paulo, Brazil.Andres, Ignasi, Univ S ao Paulo USP, Dept Comp Sci, Inst Math & Stat, Sao Paulo - Brazil
[3] Univ S ao Paulo USP, Escola Artes Ciencias & Humanidades, Sao Paulo - Brazil
Número total de Afiliações: 3
Tipo de documento: Artigo Científico
Fonte: FUNDAMENTA INFORMATICAE; v. 174, n. 1, p. 63-81, 2020.
Citações Web of Science: 0
Resumo

Contingent planning models a robot that must achieve a goal in a partially observable environment with non-deterministic actions. A solution for this problem is generated by searching in the space of belief states, where a belief state is a set of possible world states. However, if there is an unavoidable dead-end state, the robot will fail to accomplish his task. In this work, rather than limiting a contingent planning task to the agent's actions and observations, we model a planning agent that is able to proactively resort to humans for help in order to complete tasks that would be unsolvable otherwise. Our aim is to develop a symbiotic autonomous agent, that is, an agent that, proactively and autonomously, asks for human help when needed. We formalize this problem and propose an extension of a translation technique to convert the contingent planning problem with human help into a non-deterministic fully observable planning problem that can be solved by an off-the-shelf efficient FOND planner. (AU)

Processo FAPESP: 15/01587-0 - Armazenagem, modelagem e análise de sistemas dinâmicos para aplicações em e-Science
Beneficiário:João Eduardo Ferreira
Linha de fomento: Auxílio à Pesquisa - Programa eScience e Data Science - Temático