Suboptimal Criterion Learning in Static and Dynamic Environments
نویسندگان
چکیده
منابع مشابه
Suboptimal Criterion Learning in Static and Dynamic Environments
Humans often make decisions based on uncertain sensory information. Signal detection theory (SDT) describes detection and discrimination decisions as a comparison of stimulus "strength" to a fixed decision criterion. However, recent research suggests that current responses depend on the recent history of stimuli and previous responses, suggesting that the decision criterion is updated trial-by-...
متن کاملThe Effect of Basic Gymnastic Exercises in Environments with Different Colors, on Static and Dynamic Balance
The current research aims to compare the effect of basic gymnastic exercises in environments with different colors, on static and dynamic balance. Participants were 40 female students ranging in age from 8 to 10 years, who were classified into three groups: "exercise in the environment with warm colors", "exercise in the environment with cool colors" and "exercise in the environment with compou...
متن کاملSTATIC AND DYNAMIC OPPOSITION-BASED LEARNING FOR COLLIDING BODIES OPTIMIZATION
Opposition-based learning was first introduced as a solution for machine learning; however, it is being extended to other artificial intelligence and soft computing fields including meta-heuristic optimization. It not only utilizes an estimate of a solution but also enters its counter-part information into the search process. The present work applies such an approach to Colliding Bodies Optimiz...
متن کاملLearning from Demonstration in Static Environment and Generalizing to Dynamic Environments
Robot learning from demonstration has been successfully used, in industrial environments, to increase the speed and reduce the complexity of the programming phase. A major challenge, however, consists in enabling a robot to generalize task demonstrations to a complex dynamic environment. To tackle this problem, an approach has been proposed in [1], combining GMM/GMR and DMPs with optimal contro...
متن کاملLearning paradigms in dynamic environments
The seminar centered around problems which arise in the context of machine learning in dynamic environments. Particular emphasis was put on a couple of specific questions in this context: how to represent and abstract knowledge appropriately to shape the problem of learning in a partially unknown and complex environment and how to combine statistical inference and abstract symbolic representati...
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: PLOS Computational Biology
سال: 2017
ISSN: 1553-7358
DOI: 10.1371/journal.pcbi.1005304