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Computational approaches to variance-penalised Markov decision processes. (English) Zbl 0768.90087

Summary: This paper develops three computational approaches for solving a variance-penalised Markov decision process, viz. parametric linear programming, parametric Lagrangean programming, and a parametric policy space approach.

MSC:

90C40 Markov and semi-Markov decision processes
90C31 Sensitivity, stability, parametric optimization
90-08 Computational methods for problems pertaining to operations research and mathematical programming
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References:

[1] Bazaraa MS, Shetty CM (1979) Nonlinear programming. J Wiley & Sons, New York
[2] Carbot AV, Francis RL (1970) Solving noncovex quadratic minimisation problems by ranking the extreme points. Oper Res 18:82–86 · Zbl 0186.24201
[3] Everett H (1963) Generalised Lagrange multiplier method for solving problems of optimum allocation of resources. Oper Res 11:399–417 · Zbl 0113.14202
[4] Falk J, Hoffman KLR (1976) A successive underestimation method for concave mininisation problems. Math Oper Res 1:251–259 · Zbl 0362.90082
[5] Filar JA, Kallenberg LCM, Lee HM (1989) Variance-penalised Markov decision processes. Math Oper Res 14:147–161 · Zbl 0676.90096
[6] Kallenberg LCM (1983) Linear programming and finite Markovian control problems. (Mathematical Centrum Tract 148) Amsterdam · Zbl 0503.90061
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