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Poznyak A.S., Najim K., Gomez-Ramirez E. — Self-learning control of finite Markov chains
Poznyak A.S., Najim K., Gomez-Ramirez E. — Self-learning control of finite Markov chains



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Название: Self-learning control of finite Markov chains

Авторы: Poznyak A.S., Najim K., Gomez-Ramirez E.

Аннотация:

This rigorously focused reference/text presents a number of new and potentially useful self-learning (adaptive) control algorithms and theoretical as well as practical results for both unconstrained and constrained finite Markov chains — efficiently processing new information by adjusting control strategies directly or indirectly. Offering new material and many descriptive simulations and concrete examples, Self-Learning Control of Finite Markov Chains supplies fundamental mathematical concepts of self-learning control of constrained and unconstrained finite Markov chains...states theorems related to the convergence, the speed of convergence, and the optimal selection of the design parameters of several efficient self-learning algorithms...analyzes the asymptotic properties (convergence with probability 1 as well as convergence in the mean squares) using the Lyapunov approach and martingales theory...discusses ways that adaptive algorithms form a new estimate, incorporating new information (realizations) from the old estimate using a fixed amount of computation and memory...introduces normalization procedures and regularized Lagrange and penalty functions...showcases the novel approach of a partially frozen control strategy...examines the asymptotic properties of different algorithms derived from schemes originally used in modeling animal learning patterns...and more. Featuring highly practical MATLAB programs for instruction and elaboration of key concepts, Self-Learning Control of Finite Markov Chains is a versatile reference for electrical, electronics, control, and software engineers; mathematicians; statisticians; and economists involved in stochastic games; and an invaluable text for upper-level undergraduate and graduate students in these disciplines.


Язык: en

Рубрика: Математика/Оптимизация и управление/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 2002

Количество страниц: 298

Добавлена в каталог: 23.04.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
Absorbing      7
Accessible state      6
action      18 47 55 74 126 172
Adaptation rate      181 186
Adaptive      6 76 90 98 129 134 142 154 160 179 182
Adaptive control      77
Algebra      2—5 19 96
Aperiodic      11 24 53 70 94 123 145
Average      69 100 117 141 163 168
Borel      2
Borel — Cantelli lemma      79 155 157 185
Bush-Mosteller      48 56 75 118 128 141 153
Coefficient of ergodicity      12—13
communicating      7 10 18 21—22 184
Consistency      102 141
Convergence rate      63 83 107 136 162
Ergodic      10—11 22 24 49 52 57 70 77 129 167—168 172 179 182—183
Expectation      3—4 58 61 78 81 101 131 156
Frozen      89—90 94 168
General type      25 182
Gradient      87 89 156 168 173 183
Homogeneous      9 13 18 21
Homomorphism      109
Inequality problem      182
Inequality type problem      167
Irreducible      10 21
Lagrange      48 53—54 58 62 118 123—124 130 135
Law of Large Numbers      50 79 105
Learning      48 52 54 57 62 74 82 118 126 134 142 150 160
Lebesgue      4
Lipshitz      53 71 148
Loss function      47—48 51 69 98 100 118 121 129 142—143 174
Lyapunov      57 77 129 154
Markov      5—6 48 57 69 88 111 142 168 172 181—182
Mean squares      58 62 77 82 130 134—135 155 160
Non-return      6 10 22 183
Non-singular      19 23 52 169 183
Normalization      54 73—74 125 149
Optimization      27—28 53 57 62 70—71 76 82 87 118 122 124 135 143 147—148 154 167 182 185
Penalty function      69—70 78 82 141 147 155
periodicity      10
probability      2—3 8 77 82 97 102 134 142 155 169
Programming problem      64 70 72 84 90 111 118 122 136 144 162
Projection      73 87—90 99 168 173 183
Randomized control      19
Recurrent      7
Regular      11 24 26 71 94 124 171 179
Robbins-Siegmund      62 81 93 97 134 155 160
Rozanov      13 94 171
Saddle point      53 124
simplex      53 71 124 147
Sragovitch      21
State      5 7 10 74 88 91 94 118 127
Stationary distribution      12—13
Stochastic matrix      9 74 169 171
Strategy      18
toeplitz      17 105 176—177
Transient      7
Transition matrix      8—9 13 20—21 52 87 94 123 145 171
Tsetlin      28
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