Rollout Algorithms for Constrained Dynamic Programming

نویسنده

  • Dimitri P. Bertsekas
چکیده

The rollout algorithm is a suboptimal control method for deterministic and stochastic problems that can be solved by dynamic programming. In this short note, we derive an extension of the rollout algorithm that applies to constrained deterministic dynamic programming problems, and relies on a suboptimal policy, called base heuristic. Under suitable assumptions, we show that if the base heuristic produces a feasible solution, the rollout algorithm also produces a feasible solution, whose cost is no worse than the cost corresponding to the base heuristic. 1 Supported by NSF Grant ECS-0218328. 2 Dept. of Electrical Engineering and Computer Science, M.I.T., Cambridge, Mass., 02139.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

LIDS 2646 Rollout Algorithms for Constrained Dynamic Programming

The rollout algorithm is a suboptimal control method for deterministic and stochastic problems that can be solved by dynamic programming. In this short note, we derive an extension of the rollout algorithm that applies to constrained deterministic dynamic programming problems, and relies on a suboptimal policy, called base heuristic. Under suitable assumptions, we show that if the base heuristi...

متن کامل

Dynamic Programming and Suboptimal Control: A Survey from ADP to MPC1

We survey some recent research directions within the field of approximate dynamic programming (ADP), with a particular emphasis on rollout algorithms and model predictive control (MPC). We argue that while motivated by different concerns, these two methodologies are closely connected, and the mathematical essence of their desirable properties (cost improvement and stability, respectively) is co...

متن کامل

Dynamic Programming and Suboptimal Control: A Survey from ADP to MPC

We survey some recent research directions within the field of approximate dynamic programming, with a particular emphasis on rollout algorithms and model predictive control (MPC). We argue that while they are motivated by different concerns, these two methodologies are closely connected, and the mathematical essence of their desirable properties (cost improvement and stability, respectively) is...

متن کامل

Average-Case Performance of Rollout Algorithms for Knapsack Problems

Rollout algorithms have demonstrated excellent performance on a variety of dynamic and discrete optimization problems. Interpreted as an approximate dynamic programming algorithm, a rollout algorithm estimates the value-to-go at each decision stage by simulating future events while following a heuristic policy, referred to as the base policy. While in many cases rollout algorithms are guarantee...

متن کامل

Navigation In GPS-Denied Environments Using Approximate Dynamic Programming

Controlling a mobile vehicle to navigate in GPS-denied environments introduces a challenging partially observable control problem with complex constraints. This report presents a combination of various suboptimal control schemes such as open loop feedback control (OLFC), certainty equivalent control (CEC), model predictive control (MPC), and using expected values of estimates as full states to ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009