Join our meetup, learn, connect, share, and get to know your Toronto AI community.
Browse through the latest deep learning, ai, machine learning postings from Indeed for the GTA.
Are you looking to sponsor space, be a speaker, or volunteer, feel free to give us a shout.
Hello I want to create a deep Q learning agent for a 2 player board game. My rewards are 250 for winning the game, 100, 80 and 50 for “good” moves. My tutor said to me that I should normalize the rewards because there are only limited amounts of different rewards and there are possibly infinitely manyQ values. How should I normalize the rewards? Should I normalize the rewards to [0,1] range so that 0,8 represents a game winning move, 0,3 a good move for example?
submitted by /u/Kralex68
[link] [comments]