Search Results for "algorithms"

Train and embed intelligent agents by leveraging state-of-the-art deep learning technology. Creating responsive and intelligent virtual players and non-playable game characters is hard. Especially when the game is complex. To create intelligent behaviors, developers have had to resort to writing tons of code or using highly specialized tools. With Unity Machine Learning Agents (ML-Agents), you are no longer “coding” emergent behaviors, but rather teaching intelligent agents to “learn”...

The Accord.NET Framework provides machine learning, mathematics, statistics, computer vision, computer audition, and several scientific computing related methods and techniques to .NET. The project is compatible with the .NET Framework. NET Standard, .NET Core, and Mono.

Multiple Back-Propagation is an open source software application for training neural networks with the backpropagation and the multiple back propagation algorithms. Currently this project is also hosted at http://code.google.com/p/multiplebackpropagation

Application allowing convenient experimentation in Reinforcement Learning - a Machine Learning domain. Project goals are: - keep adding new environments and agents as simple as possible - provide a rich set of state-of-art algorithms and problems - integrate with other existing Reinforcement Learning platforms If you found this application useful please cite this work: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6643987

...It is probably best compared to a database management system, but for neural networks instead of relational data. As such, the library is optimized for handling any type of data-size by using advanced streaming and caching algorithms. With the designer, you are able to create different types of decision trees, random forests, n-grams, pattern-matchers, conversational agents and all sorts of AI related algorithms. You can combine statistical approaches as well as pattern matchers or others. Do natural language processing, image or data analysis & interpretation,...

SVM# is a svm(support vector machine) classification implemented in C#. The project contains both train and predict modules.

Very basic cellular automaton implementation in C#. Based upon the "Togetherness" algorithm described at http://www.hermetic.ch/pca/tg.htm.

Example of using Neural networks to implement chase between mouses and cats. Mouses search for cheese on map, while cats are chasing mouses. Goal of the project is to see will both sides learn some new behavior over time using genetic algorithms.