Tic-Tac-Toe


Part 4 -- Neural Network Q Learning, a Tic Tac Toe player that learns -- kind of

#artificialintelligence

Not as good as I would have hoped given that mastering Tic Tac Toe is not a particularly hard challenge -- at least for a human, even of very young age.


A Data-Efficient Deep Learning Approach for Deployable Multimodal Social Robots

arXiv.org Artificial Intelligence

The deep supervised and reinforcement learning paradigms (among others) have the potential to endow interactive multimodal social robots with the ability of acquiring skills autonomously. But it is still not very clear yet how they can be best deployed in real world applications. As a step in this direction, we propose a deep learning-based approach for efficiently training a humanoid robot to play multimodal games---and use the game of `Noughts & Crosses' with two variants as a case study. Its minimum requirements for learning to perceive and interact are based on a few hundred example images, a few example multimodal dialogues and physical demonstrations of robot manipulation, and automatic simulations. In addition, we propose novel algorithms for robust visual game tracking and for competitive policy learning with high winning rates, which substantially outperform DQN-based baselines. While an automatic evaluation shows evidence that the proposed approach can be easily extended to new games with competitive robot behaviours, a human evaluation with 130 humans playing with the Pepper robot confirms that highly accurate visual perception is required for successful game play.


r/MachineLearning - [D] How to create a neural network for the game Ult. tic tac toe?

#artificialintelligence

Hello I want to create a neural network for the game Ult. It is my first neural network that I will create. I want to have 90 inputs to the layer(81 representing the sub boards and 9 the global boards, -1 for occupied by O, 0 for empty and 1 for occupied by X). I want to include one or two hidden layers with 40 nodes each(Sigmoid function). The output layer has 1 output node ranging from [-1,1] representing 1 that X will win and -1 that O will win.


A Tic Tac Toe AI with Neural Networks and Machine Learning

#artificialintelligence

This article is my entry for CodeProject's AI competition "Image Classification Challenge"[ ]. My goal was to teach a neural network to play a game of tic tac toe, starting from only knowing the rules. Tic tac toe is a solved game. A perfect strategy[ ] exists so a neural network is a bit overkill and will not perform as well as existing programs and humans can. Described from a high level: when the AI needs to make a move, it iterates over all possible moves, generates the board after making a given move, and uses the neural network to see how good the position is after performing that move.


Tic Tac Toe - Creating Unbeatable AI – Towards Data Science

#artificialintelligence

In today's article, I am going to show you how to create an unbeatable AI agent that plays the classic Tic Tac Toe game. You will learn the concept of the Minimax algorithm that is widely and successfully used across the fields like Artificial Intelligence, Economics, Game Theory, Statistics or even Philosophy. Before we go into the AI part, let's make sure that we understand the game. I recommend you to play the game yourself, feel free to check out my iOS Tic Tac Toe app.


When Bots Teach Themselves to Cheat

#artificialintelligence

Once upon a time, a bot deep in a game of tic-tac-toe figured out that making improbable moves caused its bot opponent to crash. Moments when experimental bots go rogue--some would call it cheating--are not typically celebrated in scientific papers or press releases. Most AI researchers strive to avoid them, but a select few document and study these bugs in the hopes of revealing the roots of algorithmic impishness. "We don't want to wait until these things start to appear in the real world," says Victoria Krakovna, a research scientist at Alphabet's DeepMind unit. Krakovna is the keeper of a crowdsourced list of AI bugs.


This Rehab Robot Will Challenge You to Tic-Tac-Toe

IEEE Spectrum Robotics

Physical rehabilitation is not something that anyone does for fun. You do it grudgingly, after an illness or accident, to try and slowly drag your body back toward what it was able to do before. I've been there, and it sucks. I wasn't there for nearly as long as I should have been, however: rehab was hard and boring, so I didn't properly finish it. Researchers at Ben-Gurion University of the Negev in Israel, led by Shelly Levy-Tzedek, have been experimenting with ways of making rehab a bit more engaging with the addition of a friendly robot arm.


Announcing TensorFlow 1.5

#artificialintelligence

Is there an SDK to use TensorFlow Lite in Java/Kotlin? Also, is it possible to do other things in TensorFlow Lite, other than image related things? For example, teach it to win tick-tack-toe by itself? You'd think the leaders in machine learning would be able to prevent comment spam by now, especially on their own blog....


Announcing TensorFlow 1.5

#artificialintelligence

Is there an SDK to use TensorFlow Lite in Java/Kotlin? Also, is it possible to do other things in TensorFlow Lite, other than image related things? For example, teach it to win tick-tack-toe by itself? You'd think the leaders in machine learning would be able to prevent comment spam by now, especially on their own blog.... As spam goes, this one is pretty entertaining though...:D


Menace: the Machine Educable Noughts And Crosses Engine - Chalkdust

#artificialintelligence

The use of machine learning to teach computers to play board games has had a lot of interest lately. Big companies such as Facebook and Google have both made recent breakthroughs in teaching AI the complex board game, Go. However, people have been using machine learning to teach computers board games since the mid-twentieth century. In the early 1960s Donald Michie, a British computer scientist who helped break the German Tunny code during the Second World War, came up with Menace (the Machine Educable Noughts And Crosses Engine). Menace uses 304 matchboxes all filled with coloured beads in order to learn to play noughts and crosses.