Detection theory | Search algorithms | Theorems in discrete mathematics | Decision theory | Fixed points (mathematics) | Game theory | Optimization algorithms and methods | Graph algorithms
Minimax (sometimes MinMax, MM or saddle point) is a decision rule used in artificial intelligence, decision theory, game theory, statistics, and philosophy for minimizing the possible loss for a worst case (maximum loss) scenario. When dealing with gains, it is referred to as "maximin" – to maximize the minimum gain. Originally formulated for several-player zero-sum game theory, covering both the cases where players take alternate moves and those where they make simultaneous moves, it has also been extended to more complex games and to general decision-making in the presence of uncertainty. (Wikipedia).
A Liter Of Light *Official Version*
Check out this mini-docu that we shot! http://www.playwiththejunglegym.com/
From playlist Amazing Stuff
From playlist the absolute best of stereolab
From playlist the absolute best of stereolab
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From playlist Science Unplugged: General Relativity
From playlist the absolute best of stereolab
What is length contraction? Length contraction gives the second piece (along with time dilation) of the puzzle that allows us to reconcile the fact that the speed of light is constant in all reference frames.
From playlist Relativity
Coding Challenge 154: Tic Tac Toe AI with Minimax Algorithm
In this challenge I take the Tic Tac Toe game from coding challenge #149 and add an AI opponent for a human player by implenenting the Minimax algorithm. Code: https://thecodingtrain.com/challenges/154-tic-tac-toe-minimax 🕹️ p5.js Web Editor Sketch: https://editor.p5js.org/codingtrain/ske
From playlist Coding Challenges
Learning Minimax Estimators Via Online Learning by Praneeth Netrapalli
PROGRAM: ADVANCES IN APPLIED PROBABILITY ORGANIZERS: Vivek Borkar, Sandeep Juneja, Kavita Ramanan, Devavrat Shah, and Piyush Srivastava DATE & TIME: 05 August 2019 to 17 August 2019 VENUE: Ramanujan Lecture Hall, ICTS Bangalore Applied probability has seen a revolutionary growth in resear
From playlist Advances in Applied Probability 2019
Minimax Approximation and the Exchange Algorithm
In this video we'll discuss minimax approximation. This is a method of approximating functions by minimisation of the infinity (uniform) norm. The exchange algorithm is an iterative method of finding the approximation which minimises the infinity norm. FAQ : How do you make these animatio
From playlist Approximation Theory
Minimax Algorithm in Artificial Intelligence | Minimax Algorithm Explained | AI Tutorial|Simplilearn
🔥 Professional Certificate Program In AI And Machine Learning: https://www.simplilearn.com/pgp-ai-machine-learning-certification-training-course?utm_campaign=7April2023MinimaxAlgorithminArtificialIntelligence&utm_medium=DescriptionFirstFold&utm_source=youtube 🔥 Artificial Intellig
JavaScript Tic Tac Toe Project Tutorial - Unbeatable AI w/ Minimax Algorithm
A full web development tutorial for beginners that demonstrates how to create an unbeatable tic tac toe game using vanilla JavaScript, HTML, and CSS. Learn the Minimax algorithm! ⌨ Part 1: Introduction (0:00) Code: none ⌨ Part 2: HTML (2:58) Code: https://github.com/beaucarnes/fcc-projec
From playlist JavaScript Tutorials
Martin Wainwright: Privacy and statistical minimax: quantitative tradeoffs
Find this video and other talks given by worldwide mathematicians on CIRM's Audiovisual Mathematics Library: http://library.cirm-math.fr. And discover all its functionalities: - Chapter markers and keywords to watch the parts of your choice in the video - Videos enriched with abstracts, b
From playlist Probability and Statistics
Reinforcement Learning 10: Classic Games Case Study
David Silver, Research Scientist, discusses classic games as part of the Advanced Deep Learning & Reinforcement Learning Lectures.
From playlist DeepMind x UCL | Reinforcement Learning Course 2018
Game Playing 1 - Minimax, Alpha-beta Pruning | Stanford CS221: AI (Autumn 2019)
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3Cke8v4 Topics: Minimax, expectimax, Evaluation functions, Alpha-beta pruning Percy Liang, Associate Professor & Dorsa Sadigh, Assistant Professor - Stanford Univer
From playlist Stanford CS221: Artificial Intelligence: Principles and Techniques | Autumn 2021
Nonconvex Minimax Optimization - Chi Ji
Seminar on Theoretical Machine Learning Topic: Nonconvex Minimax Optimization Speaker: Chi Ji Affiliation: Princeton University; Member, School of Mathematics Date: November 20, 2019 For more video please visit http://video.ias.edu
From playlist Mathematics
Fastest Identification in Linear Systems by Alexandre Proutiere
Program Advances in Applied Probability II (ONLINE) ORGANIZERS: Vivek S Borkar (IIT Bombay, India), Sandeep Juneja (TIFR Mumbai, India), Kavita Ramanan (Brown University, Rhode Island), Devavrat Shah (MIT, US) and Piyush Srivastava (TIFR Mumbai, India) DATE: 04 January 2021 to 08 Januar
From playlist Advances in Applied Probability II (Online)