Focused crawls are collections of frequently-updated webcrawl data from narrow (as opposed to broad or wide) web crawls, often focused on a single domain or subdomain.
A 2D Unity simulation in which cars learn to navigate themselves through different courses. The cars are steered by a feedforward neural network. The weights of the network are trained using a modified genetic algorithm.
A possible improvement of the time series smoothing operation is proposed. Below is example of applying smoothed operation
Currently, the implementation of smoothing allows modifying only the "features" time series (features field in InputData/OutputData). But it does not change the
Always sparse. Never dense. But never say never. A Sparse Training repository for the Adaptive Sparse Connectivity concept and its algorithmic instantiation, i.e. Sparse Evolutionary Training, to boost Deep Learning scalability on various aspects (e.g. memory and computational time efficiency, representation and generalization power).
The first open-source AI-driven tool for automatically generating system-level test cases (also known as fuzzing) for web/enterprise applications. Currently targeting whitebox and blackbox testing of REST APIs.
Forex trading simulator environment for OpenAI Gym, observations contain the order status, performance and timeseries loaded from a CSV file containing rates and indicators. Work In Progress
KaHyPar (Karlsruhe Hypergraph Partitioning) is a multilevel hypergraph partitioning framework providing direct k-way and recursive bisection based partitioning algorithms that compute solutions of very high quality.
The attr ranges could accept an interval of chars (according to ASCII). The attr ranges are mainly used by the plugins to define their attributes, e.g., see the attributes of this plugin.
One of the strengths of evolution strategy algorithm is its linear scalability.
Thus it would be great to have this implemented in Evostra.