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1
Further Topics on Discrete-Time Markov Control Processes
Springer-Verlag New York
Onésimo Hernández-Lerma
,
Jean Bernard Lasserre (auth.)
function
theorem
policy
optimal
markov
assumption
dylx
satisfies
optimality
equation
proposition
finite
linear
lemma
remark
exists
functions
suppose
norm
decision
stationary
consider
policies
programming
continuous
expected
deterministic
inequality
moreover
positive
average
solution
bounded
initial
yields
implies
satisfied
prove
discounted
assumptions
criteria
total
measurable
kernel
measures
canonical
existence
poisson
arbitrary
stochastic
Year:
1999
Language:
english
File:
PDF, 4.35 MB
Your tags:
0
/
0
english, 1999
2
Discrete-Time Markov Control Processes: Basic Optimality Criteria
Springer-Verlag New York
Onésimo Hernández-Lerma
,
Jean Bernard Lasserre (auth.)
theorem
function
markov
policy
optimal
dylx
assumption
average
programming
linear
optimality
discounted
measurable
stochastic
functions
discount
hernandez
proposition
compact
lerma
satisfies
finite
probability
lemma
processes
policies
equation
app
bounded
exists
continuous
dynamic
borel
mcps
implies
remark
convergence
yields
moreover
horizon
stationary
suppose
approach
iteration
initial
feasible
inequality
models
references
solution
Year:
1996
Language:
english
File:
PDF, 5.14 MB
Your tags:
5.0
/
0
english, 1996
3
Stochastic Optimal Control: The Discrete Time Case
Elsevier, Academic Press
Dimitri P. Bertsekas and Steven E. Shreve (Eds.)
proposition
borel
measurable
optimal
policy
function
lemma
exists
spaces
xes
q.e.d
stochastic
functions
corollary
defined
define
sets
analytic
assumption
horizon
policies
finite
probability
models
universally
semicontinuous
programming
infinite
mapping
subset
assumptions
topology
metric
limit
theorem
dynamic
implies
metrizable
continuous
assume
compact
stationary
existence
markov
kernel
subsets
algorithm
countable
measures
separable
Year:
1978
Language:
english
File:
PDF, 4.60 MB
Your tags:
0
/
0
english, 1978
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