Multistage decision-making in robots involved in real-world tasks is a process affected by uncertainty. The effects of the agent’s actions in a physical en- vironment cannot be always predicted deterministically and in a precise manner. Moreover, observing the environment can be a too onerous for a robot, hence not continuos. Markov Decision Processes (MDPs) are a well-known solution inspired to the classic probabilistic approach for managing uncertainty. On the other hand, including fuzzy logics and possibility theory has widened uncertainty representa- tion. Probability, possibility, fuzzy logics, and epistemic belief allow treating dif- ferent and not always superimposable facets of uncertainty. This paper presents a new extended version of MDP, designed for managing all these kinds of uncertainty together to describe transitions between multi-valued fuzzy states. The motivation of this work is the design of robots that can be used to make decisions over time in an unpredictable environment. The model is described in detail along with its computational solution.

Cannella, V., Pirrone, R., Chella, A. (2012). Comprehensive Uncertainty Management in MDPs. In Biologically Inspired Cognitive Architectures 2012 - Proceedings of the Third Annual Meeting of the BICA Society (pp.89-94). Heidelberg : Springer [10.1007/978-3-642-34274-5_20].

Comprehensive Uncertainty Management in MDPs

CANNELLA, Vincenzo;PIRRONE, Roberto;CHELLA, Antonio
2012-01-01

Abstract

Multistage decision-making in robots involved in real-world tasks is a process affected by uncertainty. The effects of the agent’s actions in a physical en- vironment cannot be always predicted deterministically and in a precise manner. Moreover, observing the environment can be a too onerous for a robot, hence not continuos. Markov Decision Processes (MDPs) are a well-known solution inspired to the classic probabilistic approach for managing uncertainty. On the other hand, including fuzzy logics and possibility theory has widened uncertainty representa- tion. Probability, possibility, fuzzy logics, and epistemic belief allow treating dif- ferent and not always superimposable facets of uncertainty. This paper presents a new extended version of MDP, designed for managing all these kinds of uncertainty together to describe transitions between multi-valued fuzzy states. The motivation of this work is the design of robots that can be used to make decisions over time in an unpredictable environment. The model is described in detail along with its computational solution.
Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni
nov-2012
Third Annual Meeting of the BICA Society - BICA 2012
Palermo, Italy
Oct. 31 - Nov. 3, 2012
6
Cannella, V., Pirrone, R., Chella, A. (2012). Comprehensive Uncertainty Management in MDPs. In Biologically Inspired Cognitive Architectures 2012 - Proceedings of the Third Annual Meeting of the BICA Society (pp.89-94). Heidelberg : Springer [10.1007/978-3-642-34274-5_20].
Proceedings (atti dei congressi)
Cannella, V; Pirrone, R; Chella, A
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/76928
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