[BCF+13]
T. Brázdil, T. Chen, V. Forejt, P. Novotný, and A. Simaitis.
Solvency Markov Decision Processes with Interest.
In Anil Seth and Nisheeth K. Vishnoi (editors), IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2013), volume 24 of Leibniz International Proceedings in Informatics (LIPIcs), pages 487-499, Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik.
2013.
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Abstract.
Solvency games, introduced by Berger et al., provide an abstract framework for modelling
decisions of a risk-averse investor, whose goal is to avoid ever going broke. We study a new
variant of this model, where, in addition to stochastic environment and fixed increments and
decrements to the investor’s wealth, we introduce interest, which is earned or paid on the current
level of savings or debt, respectively.
We study problems related to the minimum initial wealth sufficient to avoid bankruptcy
(i.e. steady decrease of the wealth) with probability at least p. We present an exponential time
algorithm which approximates this minimum initial wealth, and show that a polynomial time
approximation is not possible unless P = NP. For the qualitative case, i.e. p = 1, we show
that the problem whether a given number is larger than or equal to the minimum initial wealth
belongs to NP ∩ coNP, and show that a polynomial time algorithm would yield a polynomial
time algorithm for mean-payoff games, existence of which is a longstanding open problem. We
also identify some classes of solvency MDPs for which this problem is in P. In all above cases the
algorithms also give corresponding bankruptcy avoiding strategies.
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