A generic, simple and fast implementation of Deepmind's AlphaZero
Beyond its much publicized success in attaining superhuman level at games such as Chess and Go, DeepMind's AlphaZero algorithm illustrates a more general methodology of combining learning and search to explore large combinatorial spaces effectively. We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C++)...
A Chinese chess game including an adaptive computer opponent.
This project is an application of POSM algorithm on Chinese chess computer player.
A computer player is implemented, which will adapt to the its opponent by adjusting its playing strength accordingly.
A simple application for displaying time-remaining for an event, such as for cooking, chess playing, debate speech timing, or governing floor-time at a public speaking event, such as paper presentations. The numbers appear large enough to be seen at a distance, or the display can be shrunk into the corner of a presentation screen. The time-remaining display changes color, as a warning, near end of the duration. Display also shows elapsed time, and has a pause/resume button. The...
Give your IT, operations, and business teams the ability to deliver exceptional services—without the complexity.
Freshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
CINAG is an UCI computer chess engine. This is a module which thinks about the game and try to find the best move for each position. Our goal is to create a quite strong opponent by using state of the art AI technics.
SMART: SMART Minimax Analyser for Recursive Trees. The goal of the SMART project is to develop a powerful state-of-the art FICS compliant chess engine, using experimental technology (re-iterative MTDf , ETC, reinforced temporal difference learning, etc.)