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Statistics 125: Games, Gambling and Coincidences. Emphasizes problem solving and modeling related to games, gambling and coincidences, touching on many fundamental ideas in discrete probability, finite Markov chains, dynamic programming and game theory. (First Year Seminar) (3 Credits) Statistics 150: Making Sense of Data
DTIC AD0750285: Dynamic Programming and Gambling Models In the paper the author formulates and obtains optimal gambling strategies for certain gambling models. This is done by setting these models within the framework of dynamic programming (also referred to as Markovian decision processes) and then using results in this field. Introduction to Stochastic Dynamic Programming of stochastic dynamic programming. Chapter I is a study of a variety of finite-stage models, illustrating the wide range of applications of stochastic dynamic programming. Later chapters study infinite-stage models: dis-counting future returns in Chapter II, minimizing nonnegative costs in 1 u l 'i' ' i ,,,.^. ,.»p.,.., inim.j„V(iiiiiiiiiM in certain gambling models. We do this by setting these models within the framework of dynamic programming (also referred to as Markovian decision processes) and then utilize results in this field. In Section 2 we present some dynamic programming results. In partic- ular we review and expand upon two of the main results in dynamic programming.
Dynamic programming-based multi-vehicle longitudinal…
Optimization and Control 1 Dynamic Programming: The Optimality Equation We introduce the idea of dynamic programming and the principle of optimality. We give notation for state-structured models, and introduce ideas of feedback, open-loop, and closed-loop controls, a Markov decision process, and the idea that it can be useful to model things in terms of time to go. Dynamic programming and the evaluation of gaming designs ... Since their invention before the beginning of the last century, slot machines have evolved to become the most profitable form of gambling activity for land-based casinos. Now the potential exists for... Dynamic programming and optimal control in SearchWorks catalog
Chapter 12 Dynamic Programming
In the paper the author formulates and obtains optimal gambling strategies for certain gambling models. This is done by setting these models within the framework of dynamic programming (also referred to as Markovian decision processes) and then using results in this field. Dynamic programming and the evaluation of gaming designs Dynamic programming is used to solve some simple gambling models. In particular we consider the situation where an individual may bet any integral amount not greater than his fortune and he will ... Dynamic programming and the evaluation of gaming designs ... Decision tree analysis was used for a previous evaluation of HI-LO. In contrast the assessment that follows is based on a stochastic dynamic programming (DP) (backward recursion) analysis – the default methodology in the industry. Corresponding results for a real-life test application confirm the superiority of the DP approach. Introduction to Stochastic Dynamic Programming
Dynamic programming is both a mathematical optimization method and a computer programming method. The method was developed by Richard Bellman in the 1950s and has found applications in...
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Mathematical Methods • Programming Models • Mathematical and Simulation Modeling