An Improved Reinforcement Learning System Using Affective Factors
نویسندگان
چکیده
منابع مشابه
An Improved Reinforcement Learning System Using Affective Factors
As a powerful and intelligent machine learning method, reinforcement learning (RL) has been widely used in many fields such as game theory, adaptive control, multi-agent system, nonlinear forecasting, and so on. The main contribution of this technique is its exploration and exploitation approaches to find the optimal solution or semi-optimal solution of goal-directed problems. However, when RL ...
متن کاملImproved Dynamic Stability Using Reinforcement Learning
Many researchers studying legged locomotion have applied tools from reinforcement learning/optimal control to minimize characteristics of a walking gait, most notably the energy consumption. In this paper, we use similar tools to maximize the region of stability of the controller defined as the set of initial conditions from which the robot maintains its balance for at least 5 seconds. Experime...
متن کاملAn Adaptive Learning Game for Autistic Children using Reinforcement Learning and Fuzzy Logic
This paper, presents an adapted serious game for rating social ability in children with autism spectrum disorder (ASD). The required measurements are obtained by challenges of the proposed serious game. The proposed serious game uses reinforcement learning concepts for being adaptive. It is based on fuzzy logic to evaluate the social ability level of the children with ASD. The game adapts itsel...
متن کاملAn automated FX trading system using adaptive reinforcement learning
This paper introduces adaptive reinforcement learning (ARL) as the basis for a fully automated trading system application. The system is designed to trade FX markets and relies on a layered structure consisting of a machine learning algorithm, a risk management overlay and a dynamic utility optimization layer. An existing machine-learning method called recurrent reinforcement learning (RRL) was...
متن کاملPersonalized Intelligent Tutoring System Using Reinforcement Learning
In this paper, we present a Personalized Intelligent Tutoring System that uses Reinforcement Learning techniques to implicitly learn teaching rules and provide instructions to students based on their needs. The system works on coarsely labeled data with minimum expert knowledge to ease extension
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: Robotics
سال: 2013
ISSN: 2218-6581
DOI: 10.3390/robotics2030149