BASKETBOL TAKIMLARININ TEKNİK PERFORMANSLARININ CRITIC-MOOSRA YÖNTEMİ İLE DEĞERLENDİRİLMESİ
نویسندگان
چکیده
منابع مشابه
A critic-critic architecture to combine reinforcement and supervised learnings
In real life, learning is greatly speeded-up by the intervention of a teacher who gives examples, or shows, how to perform a certain task. In all this abstract, we let apart structural simpli cations of the problem by the designer which to not deal explicitely with learning. The intervention of the teacher can be realized in di erent ways: verbal explanation, demonstration, guidance, shaping th...
متن کاملYazilim Gelistirme Takimlarinin Bulut Ustunden Yazilim Gelistirme Egilimlerinin Incelenmesi
Today, Cloud Computing offers attractive and effective solutions for organizations which enable them to decrease IT costs, provide flexibility to services and make it easier to access IT services – therefore enable faster market entries. For an organization that decides to make use of Cloud services, there are various factors to evaluate similar to outsourcing. In this paper, we studied these f...
متن کاملHierarchical Actor-Critic
The ability to learn at different resolutions in time may help overcome one of the main challenges in deep reinforcement learning — sample efficiency. Hierarchical agents that operate at different levels of temporal abstraction can learn tasks more quickly because they can divide the work of learning behaviors among multiple policies and can also explore the environment at a higher level. In th...
متن کاملThe Eigenoption-Critic Framework
Eigenoptions (EOs) have been recently introduced as a promising idea for generating a diverse set of options through the graph Laplacian, having been shown to allow efficient exploration Machado et al. [2017a]. Despite its first initial promising results, a couple of issues in current algorithms limit its application, namely: 1) EO methods require two separate steps (eigenoption discovery and r...
متن کاملProjected Natural Actor-Critic
Natural actor-critics form a popular class of policy search algorithms for finding locally optimal policies for Markov decision processes. In this paper we address a drawback of natural actor-critics that limits their real-world applicability—their lack of safety guarantees. We present a principled algorithm for performing natural gradient descent over a constrained domain. In the context of re...
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: International Journal of Social Humanities Sciences Research (JSHSR)
سال: 2018
ISSN: 2459-1149
DOI: 10.26450/jshsr.817