# Haut PDF On Submodular Value Functions of Dynamic Programming

### On Submodular Value Functions of Dynamic Programming

27

### On Aggregators and Dynamic Programming

**of**a solution to the Bellman ...possibility

**of**identifying a pair

**of**

**functions**v and v which fullfils the assumptions

**of**this ...class

**of**examples is useful as it ...

33

### Dynamic programming for optimal control of stochastic McKean-Vlasov dynamics

**of**the

**value**function in the Wasserstein space

**of**probability measures, we are able to prove a

**dynamic**

**programming**principle (DPP) for our stochastic McKean-Vlasov control ...

34

### Dynamic programming approach to principal-agent problems

**of**our paper is the following: we provide a systematic method to solve any problem

**of**this sort, including those in which Agent can also control the volatility

**of**the output process, and ...

29

### Approximate dynamic programming with a fuzzy parameterization

**dynamic**

**programming**, fuzzy approximation,

**value**iteration, convergence ...Introduction

**Dynamic**

**programming**(DP) is a powerful paradigm for solving optimal control problems, ...

14

### Value function for regional control problems via dynamic programming and Pontryagin maximum principle

**of**the state space and present discontinuities at their ...number

**of**switchings (no Zeno phenomenon), we use the duplication technique to show that the

**value**function

**of**the regional ...

26

### Approximating Submodular Functions Everywhere

**functions**motivates us to investigate other fun- damental questions concerning their ...a

**submodular**func- tion? How much

**of**that information can be obtained in just a few

**value**oracle ...

11

### Allowing non-submodular score functions in distributed task allocation

**value**because

**of**the presence

**of**other assign- ...score

**functions**typically used in task allocation satisfy this submodularity condition (for example the information theory community [10]), ...

9

### Metric Learning with Submodular Functions

**of**KNN with different metrics learning algorithm and their running time in ...ξ

**of**the ξ-additive varies from 1 to min(10, m). A

**value**

**of**ξ = 1 means that there is no interaction be- ...

18

### An approximate dynamic programming approach to solving dynamic oligopoly models

**of**this approximation architecture makes the linear program in Algorithm 3 a tractable ...millions

**of**billions states only thousands

**of**basis

**functions**are ...selection

**of**basis ...

48

### Air-Combat Strategy Using Approximate Dynamic Programming

**of**the dangerous missions currently flown by manned ...complexity

**of**some tasks, such as air combat, have precluded UAS from successfully carrying out these missions ...formulation

**of**a level ...

34

### A CMOS Current-Mode Dynamic Programming Circuit

**of**“curse

**of**dimensionality” as coined by Bellman in [10] refers to the vast computational effort required for the numerical solution

**of**Bellman’s equation when there is a large number ...

13

### Branch-and bound strategies for dynamic programming

68

### Branch-and-bound strategies for dynamic programming

66

### Dynamic Programming for Mean-Field Type Control

**of**the HJB

**dynamic**

**programming**...well-posedness

**of**the HJB or adjoint equation because it is set in an infinite domain in ...lack

**of**proof

**of**convergence

**of**the ...

21

### Optimal routing configuration clustering through dynamic programming

**of**traffic matrices (TMs), which might represent the evolution over time

**of**end-to-end connections ...clusters

**of**contiguous TMs with a single routing configuration applied to each ...TMs ...

5

### Local minimization algorithms for dynamic programming equations

**of**elements

**of**U (see for instance [1, 12, 17] and references ...contribution

**of**this paper is to demonstrate that an accurate realization

**of**the min-operation on the right hand side ...

28

### Risk-aware decision making and dynamic programming

**of**the ...space

**of**the agent. The random selection

**of**an action in A according to a distribution conditioned on the information state i t ∈ I is ...

8

### Adaptive aggregation methods for discounted dynamic programming

17

### Dynamic Programming for Mean-field type Control

**of**J with respect to u we have used 100 iterations

**of**a gradient method with fixed step size, ω = ...parameters

**of**the problem are T = 2, h = ...method

**of**degree 1 on a mesh ...

10