RebeccaAIML is an enterprise cross platform AIML development platform. RebeccaAIML supports C++, Java, C#, Python, and many other programming languages. It allows AIML development out of the box. RebeccaAIML also comes with an array of AIML administration tools, great documentation, and an Eclipse AIML editor plugin.
Nomatic*IM provides a service that supports the convenient and appropriate broadcasting of presence through instant messaging clients. It provides the flexibility to support multiple IM protocols, IM clients, and operating systems. From a high-level, what Nomatic*IM does is to figure out where you are and what you are doing from the sensors that come with your computing platform. That information is processed with machine learning techniques to develop a semantic interpretation about the name of your current place, activity, and social context.
Aseba is an event-based architecture for distributed control of mobile robots. It targets integrated multi-processor robots or groups of single-processor units, real or simulated. The core of aseba is a lightweight virtual machine tiny enough to run even on microcontrollers. Robots are programmed in a user-friendly scripting language using a cozy integrated development environment.
RegMAS (Regional Multi Agent Simulator) is a spatially explicit multi-agent model framework, designed for long-term simulations of effects of government policies over agricultural systems (e.g. farm sizes, incomes, land use). RegMAS uses a profit-maximization algorithm to derive farmers' behaviors. Using RegMAS, researchers can write regional-specific models, adapting the pool of activities and resources to their specific region.
MyMediaLite is a lightweight, multi-purpose library of recommender system algorithms. It addresses the two most common scenarios in collaborative filtering: rating prediction (e.g. on a scale of 1 to 5 stars), and item prediction from implicit feedback (e.g. from clicks or purchase actions). It contains dozens of recommender engines, including state-of-the-art matrix factorization methods. It also supports real-time updates to the recommender engines, storing engines to disk and reloading them again, and several evaluation measures to compare the accuracy of different recommender system methods. Three command-line programs that offer most of the functionality contained in the library are included.