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In this paper we describe an approximate dynamic programming policy for a discrete-time dynamical system perturbed by noise. The approximate value function is the pointwise supremum of a family of low...
Approximate Dynamic Programming via Iterated Bellman Inequalities
Convex Optimization Dynamic Programming Stochastic Control
2015/7/9
In this paper we introduce new methods for finding functions that lower bound the value function of a stochastic control problem, using an iterated form of the Bellman inequality. Our method is based ...
Quadratic Approximate Dynamic Programming for Input-Affine Systems
approximate dynamic programming stochastic control convex optimization
2015/7/9
We consider the use of quadratic approximate value functions for stochastic control problems with input-affine dynamics and convex stage cost and constraints. Evaluating the approximate dynamic progra...
An Approximate Dynamic Programming Approach to Decentralized Control of Stochastic Systems
Decentralized Control Dynamic Programming
2015/6/19
we consider the problem of computing decentralized control policies for stochastic systems with finite state and action spaces. Synthesis of optimal decentralized policies for such problems is known t...
An Approximate Dynamic Programming Approach to the Dynamic Traveling Repairperson Problem
Traveling Repairperson Dynamic Programming
2015/6/19
This paper presents a novel suboptimal policy for the Dynamic Traveling Repairperson Problem~(m-DTRP), a problem requiring dynamic planning for a team of vehicles. The suggested policy is adaptive, lo...
Optimization-based Approximate Dynamic Programming
Approximate Dynamic Programming Approximate Linear Programming,
2014/12/18
Reinforcement learning algorithms hold promise in many complex domains, such as resource management and planning under uncertainty. Most reinforcement learning algorithms are iterative - they successi...