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The Teachingbox uses advanced machine learning techniques to relieve developers from the programming of hand-crafted sophisticated behaviors of autonomous agents (such as robots, game players etc...) In the current status we have implemented a well founded reinforcement learning core in Java with many popular usecases, environments, policies and learners.
Obtaining the teachingbox:
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Artificial intelligent agent which uses pypy (python), nltk, PyAIML, and various other opensource libraries to make a self contained AI agent server / client enviroment. It is meant to work in Win, Mac and Linux. just unzip it into the dir which will be its home.
AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
PIQLE is a Platform Implementing Q-LEarning (and other Reinforcement Learning) algorithms in JAVA. Version 2 is a major refactoring. The core data structures and algorithms are in piqle-coreVersion2. Examples are in piqle-examplesVersion2. A complete doc
ABSim is an Agent-Object-Relationship (AOR) simulation system based on a Java program library. The development of ABSim has terminated. Its successor is <a href="http://oxygen.informatik.tu-cottbus.de/aor/?q=node/2">AOR-JSim </a>