https://sites.temple.edu/trail/files/2021/11/XieXinDamesIROS2021.pdf
Zhanteng Xie, Pujie Xin, and Philip Dames Abstract—This paper proposes a novel neural network-based control policy to enable a mobile robot to navigate safety through environments filled with both static obstacles, such as tables and chairs, and dense crowds of pedestrians. The network architecture uses early fusion to combine a short history of lidar data with kinematic data about nearby ...
https://cis.temple.edu/~ingargio/cis587/readings/id3-c45.html
Introduction ID3 and C4.5 are algorithms introduced by Quinlan for inducing Classification Models, also called Decision Trees, from data.
https://cis.temple.edu/tagit/presentations/Hopfield%20Networks%20is%20all%20you%20need.pdf
Note that there are 2,500 pixels in each image, the size of the weight matrix will be 2500 × 2500, but only learned by ONE image. Two natural problems will arise. 1) How many patterns can one
https://cis.temple.edu/~wangp/5603-AI/Project/2022S/pattersonblaker/Ward_Patterson_Final_Report.pdf
1 Abstract Minecraft has been the focus of much AI research in past years. Most recently, interest has risen in procedural generation of settlements in Minecraft, largely due to a annual competition established in 2018 called the Generative Design in Minecraft Competition. Inspired by this recent research, we aim to develop a set of algorithms that are capable of building a realistic ...