Analysis of the Risk Sensitive Value Iteration Algorithm

  • Igor Oliveira Borges USP
  • Karina Valdivia Delgado USP
  • Valdinei Freire USP

Resumo


This paper shows an empirical study of Value Iteration Risk Sensitive algorithm proposed by Mihatsch and Neuneier (2002). This approach makes use of a risk factor that allows dealing with different types of risk attitude (prone, neutral or averse) by using a discount factor. We show experiments with the domain of Crossing the River in two different scenarios and we analyze the influence of discount factor and risk factor under two aspects: optimal policy and processing time to convergence. We observed that: (i) the processing cost in extreme risk policies is high with both risk-averse and risk-prone attitude; (ii) a high discount increases time to convergence and reinforces the chosen risk attitude; and (iii) policies with intermediate risk factor values have a low computational cost and show a certain sensitivity to risk based on the discount factor.

Referências


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Publicado
22/10/2018
BORGES, Igor Oliveira; DELGADO, Karina Valdivia; FREIRE, Valdinei. Analysis of the Risk Sensitive Value Iteration Algorithm. In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 15. , 2018, São Paulo. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2018 . p. 365-376. ISSN 2763-9061. DOI: https://doi.org/10.5753/eniac.2018.4431.

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