Abstract: In this paper, we propose two simulations designed for the implementation of Q-learning on path planning. The first simulation of a modeling design using MatLab to find the best route by ...

Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field ...

This important study uses reinforcement learning to study how turbulent odor stimuli should be processed to yield successful navigation. The authors find that there is an optimal memory length over ...

ABSTRACT: Objective: To develop and validate a machine learning-based risk prediction model for postoperative nausea and vomiting (PONV) following gynecological day hysteroscopy, providing ...

Every game of chess is a dialogue - A test of intention, creativity, and learning that echoes far beyond the board. “Chess Game” isn’t just another web-based chess app; it’s a bold experiment in ...

Stochastic approximation algorithms are used to approximate solutions to fixed point equations that involve expectations of functions with respect to possibly unknown distributions. Among many ...