GENESIS (short for GEneral NEural SImulation System) is a general purpose simulation platform that was developed to support the simulation of neural systems ranging from subcellular components and biochemical reactions to complex models of single neurons, simulations of large networks, and systems-level models. It was developed as a research tool to provide a standard and flexible means for constructing structurally realistic models of biological neural systems.
ASpiReNN is a little C library (with Python bindings) which provides support for simple (leaky integrate-and-fire) spiking neural networks. It is primarily designed for highly recurrent networks, but it can also be used with multi-layer nets, though performance won't be the same. Though only Leaky integrate-and-fire (for the neurons) and Spike-Timing Dependent Plasticity (for learning rules) are currently implemented, adding new models shouldn't be too difficult.
Evolving Games for Unnatural Intelligence is a Java package for unsupervised machine learning based on Evolutionary Game Theory on directed graphs. It is able to segment data without any previuos information on the number of segments. It has no GUI, but implements generalizations of the original method proposed by Li, Chen, He and Jiang in the arxiv paper "A Novel Clustering Algorithm Based Upon Games on Evolving Network", published on 30 Dec 2008.
PSIworld (Programmable Scalable Interactive World) is a framework that provides a set of libraries, utilities, and applications to ease the implementation of dynamic artificial intelligence environments. Specifically, the development of multi-agent applications is targeted. It is designed in a generic manner so that various kinds of applications can use it. This framework not only includes pure algorithm libraries for AI computation tasks, but also a C/C++ library for distributed computation. A server-client model also involves various, concurrent visualization methods of distinct Agents or Societies.
Neural Network Framework is a C++ framework to develop, simulate, and analyze arbitrary complex neural networks. The programmer can use the classes provided to create neural networks with arbitrary topology and mixed type of neurons. It's very easy to add customized neurons and layers.
BinarySEC is an intelligent Web application firewall designed to suppress malicious traffic on Web sites and applications. Its artificial intelligence engine learns normal traffic and blocks malicious requests with very high accuracy. BinarySEC secures against a wide range of attacks, including cross-site scripting (XSS), SQL injection, command injection, PHP includes, parameter tampering, buffer overflow, directory traversal, attack obfuscation, and more. BinarySEC for Apache includes a graphical installer and a Web-based administration interface.