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Full-stack observability with actually useful AI | Grafana Cloud
Our generous forever free tier includes the full platform, including the AI Assistant, for 3 users with 10k metrics, 50GB logs, and 50GB traces.
Built on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
Platform for parallel computation in the Amazon cloud, including machine learning ensembles written in R for computational biology and other areas of scientific research. Home to MR-Tandem, a hadoop-enabled fork of X!Tandem peptide search engine.
Java based multi-agent platform built on an organizational model (agent, group, role). MadKit provides general agent facilities (lifecycle management, message passing, distribution, ...), and allows high heterogeneity in agents.
Both forward-chaining and backward-chaining rules (which may include python code) are compiled into python. Can also automatically assemble python programs out of python functions which are attached to backward-chaining rules. See pyke.sourceforge.ne
Spyse is a software framework for building multi-agent systems. It allows Python developers to build distributed intelligent systems of multiple cooperative agents based on FIPA, OWL, SOA and many others. Spyse is designed for ease-of-use and fun.
Applications contributed for URBI (Universal RealTime Behoavior Interface). URBI is a scripted command language used to control robots (AIBO pioneer..) as well as a robot-independant execution and developpement plateform. www.urbiforge.com www.gostai.com
AKIRA aims to create a C++ development framework to build cognitive architectures and complex artificial intelligent agents.Features:KQML,Fuzzy Logic,Neural Net,Fuzzy Cognitive Maps and DIPRA (a distributed BDI - Belief Desire Intention goals model)
Using this plugin-based framework, you can instantly start working on the *brain* of your bot (irc bot, chatterbot, robot, ...). With support for db, irc, logging and programming-language independent plugins, users can easily enhance the functionality.
WHEREAMI is an intelligent and self-learning network detection and configuration utility. With this capability, a user can just walk to a network range and WHEREAMI will self determine and connect to that network with relevant policies.
Sakura is a Knowledge Navigator and User Interface for UNIX, which implements HyperMedia and its own windowing and packing system, both in the main program and in an extensive API for Tcl and other languages.
This library provides a network abstraction layer for heterogenous large scale modular systems. It supports clearly specified interface definitions for communication between modules, while maximizing module indendence and adaptability.
Multi Agent based distributed application. The code can be processed over multiple common machines with fault-tolerance. It is designed to distributively run any Python's script, which can be applied to a given input data set.
Zeus Grid is a Grid Computing environment usefull to run systems in heterogenous machines at same time. In this first step, it will only compile, run and collect application results and file storage.
The purpose of this program is to prove that given a finite number of Monkeys and a finite amount of time one monkey will be able to make more money off the stock market than any human being. Checkout our web site for an uncorrupted download.
java-based complete Agent (ArtificialIntelligence) Framework with all the features you might expect in an Agent Framework: Mobility, Autonomy, Distributed communication, Agents can be written in Java, Jython, or Beanshell.
This project aims to build a full featured C++ (and possibly Python) library and associated tools which facilitate building Artificial Life simulations in a distributed environment.
JFIPA is intended to be a scalable, easy-to-deploy router and parser of messages between agents using the FIPA Agent Communication Language represented as XML
MAF (Mobile Agent Framework) is a research prototype which aims to facilitate the development and evaluation of mobile agent by providing a set of handy primitatives and simulation tools.