Control of Interbank Contagion Under Partial Information
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This paper investigates the limit behavior of Markov decision processes made of independent objects evolving in a common environment, when the number of objects (N) goes to infinity. In the finite horizon case, we show that when the number of objects becom ...
The dynamics of sales opportunities can be modelled by a Markov Decision Process. The latter can be solved by using dynamic programming and assigns to each state an optimal action. In this project, states are modelled by the number of opportunities at five ...
We consider robust feedback control of time-varying, linear discrete-time systems operating over a finite horizon. For such systems, we consider the problem of designing robust causal controllers that minimize the expected value of a convex quadratic cost ...
Institute of Electrical and Electronics Engineers2011
We consider robust feedback control of time-varying, linear discrete-time systems operating over a finite horizon. For such systems, we consider the problem of designing robust causal controllers that minimize the expected value of a convex quadratic cost ...
Institute of Electrical and Electronics Engineers2011
This paper investigates the limit behavior of Markov decision processes made of independent particles evolving in a common environment, when the number of particles goes to infinity. In the finite horizon case or with a discounted cost and an infinite hori ...
This paper is concerned with input adaptation in dynamic processes in order to guarantee feasible and optimal operation despite the presence of uncertainty. For optimal control problems having mixed control-state constraints, two sets of directions can be ...
We present a dynamic programming based solution to a stochastic reachability problem for a controlled discrete-time stochastic hybrid system. A sum-multiplicative cost function is introduced along with a corresponding dynamic recursion which quantifies the ...
This paper is concerned with input adaptation in dynamic processes in order to guarantee feasible and optimal operation despite the presence of uncertainty. For optimal control problems having terminal constraints, two sets of directions can be distinguish ...
We study the convergence of Markov Decision Processes made of a large number of objects to optimization problems on ordinary differential equations (ODE). We show that the optimal reward of such a Markov Decision Process, satisfying a Bellman equation, con ...
We study optimal fiscal policy in a monetary union where monetary policy is decided by an independent central bank. We consider a two-country model with trade in goods and assets, augmented with sticky prices, labor income taxes and stochastic government c ...