Sampled fictitious play for approximate dynamic programming
نویسندگان
چکیده
منابع مشابه
Sampled fictitious play for approximate dynamic programming
Sampled Fictitious Play (SFP) is a recently proposed iterative learning mechanism for computing Nash equilibria of non-cooperative games. For games of identical interests, every limit point of the sequence of mixed strategies induced by the empirical frequencies of best response actions that players in SFP play is a Nash equilibrium. Because discrete optimization problems can be viewed as games...
متن کاملSampled fictitious play for multi-action stochastic dynamic programs
We introduce a class of finite-horizon dynamic optimization problems that we call multiaction stochastic dynamic programs (DPs). Their distinguishing feature is that the decision in each state is a multi-dimensional vector. These problems can in principle be solved using Bellman’s backward recursion. However, complexity of this procedure grows exponentially in the dimension of the decision vect...
متن کاملParameter-Free Sampled Fictitious Play for Solving Deterministic Dynamic Programming Problems
Authors are encouraged to submit new papers to INFORMS journals by means of a style file template, which includes the journal title. However, use of a template does not certify that the paper has been accepted for publication in the named journal. INFORMS journal templates are for the exclusive purpose of submitting to an INFORMS journal and should not be used to distribute the papers in print ...
متن کاملSampled Fictitious Play is Hannan Consistent
Fictitious play is a simple and widely studied adaptive heuristic for playing repeated games. It is well known that fictitious play fails to be Hannan consistent. Several variants of fictitious play including regret matching, generalized regret matching and smooth fictitious play, are known to be Hannan consistent. In this note, we consider sampled fictitious play: at each round, the player sam...
متن کاملSampled Fictitious Play for Black-Box Stochastic Sequential Decision Problems
In this paper, we propose an algorithm based on Sampled Fictitious Play for solving finitehorizon stochastic sequential decision problems. Our method models the decision problem as a game of identical interest between multiple players, who use the history of their past plays to improve the estimate of optimal reward in the initial state. We show that this method is able to find an optimal polic...
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: Computers & Operations Research
سال: 2011
ISSN: 0305-0548
DOI: 10.1016/j.cor.2011.01.023