Markov Processes and Controlled Markov Chains

I Markov processes.- 1 Branching exit Markov system and their applications to partial differential equations.- 2 Feller transition functions, resolvent decomposition theorems, and their application in unstable denumerable Markov processes.- 3 Identifying Q-processes with a given finite ?-invariant measure.- 4 Convergence property of standard transition functions.- 5 Markov skeleton processes.- 6 Piecewise deterministic Markov processes and semi-dynamic Systems.- II Controlled Markov chains and decision processes.- 7 Average optimality for adaptive Markov control processes with unbounded costs and unknown disturbance distribution.- 8 Controlled Markov chains with utility functions.- 9 Classification problems in MDPs.- 10 Optimality conditions for CTMDP with average cost criterion.- 11 Optimal and nearly optimal policies in Markov decision chains with nonnegative rewards and risk-sensitive expected total-reward criterion.- 12 Interval methods for uncertain Markov decision processes.- 13 Constrained discounted semi-Markov decision processes.- 14 Linear program for communicating MDPs with multiple constraints.- 15 Optimal switching problem for Markov chains.- 16 Approximations of a controlled diffusion model for renewable resource exploitation.- III Stochastic processes and martingales.- 17 A Fleming-Viot process with unbounded selection, II.- 18 Boundary theory for superdiffusions.- 19 On solutions of backward stochastic differential equations with jumps and stochastic control.- 20 Doob's inequality and lower estimation of the maximum of martingales.- 21 The Hausdorff measure of the level sets of Brownian motion on the Sierpinski carpet.- 22 Monotonic approximation of the Gittins index.- IV Applications to finance, control systems and other related fields.- 23 Optimalconsumption-investment decisions allowing for bankruptcy: A brief survey.- 24 The hedging strategy of an Asian option.- 25 The pricing of options to exchange one asset for another.- 26 Finite horizon