The Free Connectionist Q-learning Java Framework is an library for developing learning systems. Keywords: qlearning, artificial intelligence, alife, neural nets, neural networks, machine learning, reinforcement learning unsupervised learning agents lejos
Categories
Algorithms, Robotics, Intelligent Agents, Reinforcement Learning Frameworks, Reinforcement Learning Libraries, Reinforcement Learning AlgorithmsLicense
GNU General Public License version 2.0 (GPLv2)Follow Elsy
Other Useful Business Software
Turn traffic into pipeline and prospects into customers
Docket is an AI-powered sales enablement platform designed to unify go-to-market (GTM) data through its proprietary Sales Knowledge Lake™ and activate it with intelligent AI agents. The platform helps marketing teams increase pipeline generation by 15% by engaging website visitors in human-like conversations and qualifying leads. For sales teams, Docket improves seller efficiency by 33% by providing instant product knowledge, retrieving collateral, and creating personalized documents. Built for GTM teams, Docket integrates with over 100 tools across the revenue tech stack and offers enterprise-grade security with SOC 2 Type II, GDPR, and ISO 27001 compliance. Customers report improved win rates, shorter sales cycles, and dramatically reduced response times. Docket’s scalable, accurate, and fast AI agents deliver reliable answers with confidence scores, empowering teams to close deals faster.
Rate This Project
Login To Rate This Project
User Reviews
-
This project has been moved to github.com : elser : connectionist-q-learning
-
Very promising project, but unfortunately not updated and the website has disappeared. It's the most straightforward and unintrusive reinforcement learning framework I've used in Java, though. It was easy to create an agent and run it in an existing environment I've been using to test different agents. The other project I tried recently -- Teachingbox -- required what seemed like a huge investment of time to redesign the test environment so that it fits into their framework.
-
It seems like you've got a really great framework here! I hope you update your site soon with more examples and newer source code! I can't find any of the source code for your examples.
-
Nice work ! Great project.