The general decision problem for Markov algorithms with axiom.
نویسندگان
چکیده
منابع مشابه
The general decision problem for Markov algorithms with axiom
Introduction* Let Mj denote the general decision problem for Markov algorithms with axiom. Of interest to us is whether or not this class of problems is as richly structured, with regard to degrees of unsolvability, as those classes studied in Hughes, Overbeek, and Singletary [2]. In this paper we shall present proofs which show this to be so. In particular we shall show that the general decisi...
متن کاملthe algorithm for solving the inverse numerical range problem
برد عددی ماتریس مربعی a را با w(a) نشان داده و به این صورت تعریف می کنیم w(a)={x8ax:x ?s1} ، که در آن s1 گوی واحد است. در سال 2009، راسل کاردن مساله برد عددی معکوس را به این صورت مطرح کرده است : برای نقطه z?w(a)، بردار x?s1 را به گونه ای می یابیم که z=x*ax، در این پایان نامه ، الگوریتمی برای حل مساله برد عددی معکوس ارانه می دهیم.
15 صفحه اولMarkov Decision Processes with General Discount Functions
In Markov Decision Processes, the discount function determines how much the reward for each point in time adds to the value of the process, and thus deeply a ects the optimal policy. Two cases of discount functions are well known and analyzed. The rst is no discounting at all, which correspond to the totaland average-reward criteria. The second case is a constant discount rate, which leads to a...
متن کاملSimulation-Based Algorithms for Markov Decision Processes
Title of Dissertation: Simulation-Based Algorithms for Markov Decision Processes Ying He, Doctor of Philosophy, 2002 Dissertation directed by: Professor Steven I. Marcus Department of Electrical & Computer Engineering Professor Michael C. Fu Department of Decision & Information Technologies Problems of sequential decision making under uncertainty are common in manufacturing, computer and commun...
متن کاملParallel Algorithms for Solving Markov Decision Process
Markov decision process (MDP) provides the foundations for a number of problems, such as artificial intelligence studying, automated planning and reinforcement learning. MDP can be solved efficiently in theory. However, for large scenarios, more investigations are needed to reveal practical algorithms. Algorithms for solving MDP have a natural concurrency. In this paper, we present parallel alg...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Notre Dame Journal of Formal Logic
سال: 1975
ISSN: 0029-4527
DOI: 10.1305/ndjfl/1093891701