ASYMPTOTIC OPTIMALITY AND RATES OF CONVERGENCE OF QUANTIZED STATIONARY POLICIES IN CONTINUOUS-TIME MARKOV DECISION PROCESSES

Asymptotic Optimality and Rates of Convergence of Quantized Stationary Policies in Continuous-Time Markov Decision Processes

This paper is concerned with the asymptotic optimality of quantized eeboo coupons stationary policies for continuous-time Markov decision processes (CTMDPs) in Polish spaces with state-dependent discount factors, where the transition rates and reward rates are allowed to be unbounded.Using the dynamic programming approach, we first establish the di

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State of the art of biochar in Ethiopia. A review

Today our planet is threatened by climate change, degradation of fertile soil (food insecurity), depletion of fossil fuel a combined by greenhouse gas emissions.The persistency of these problems forces scholars finding better solutions.Biochar becomes the prominent material to secure climate change by carbon sequestering, food security by enhancing

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Light Robust Goal Programming

Robust goal programming (RGP) is an emerging field of research in decision-making problems with multiple conflicting objectives and uncertain parameters.RGP combines robust optimization (RO) with variants of goal programming techniques to achieve stable and reliable goals for previously unspecified aspiration levels click here of the decision-maker

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