Search Results for "agents"

...It includes implementations for a wide range of AI topics such as computer vision, agent systems, federated learning, distributed systems, adversarial attacks, and generative AI. Many of the tutorials focus on building AI agents, multi-agent systems, and workflows that integrate language models with external tools or APIs. The codebase acts as a hands-on learning resource, allowing users to experiment with new frameworks, architectures, and machine learning workflows through guided examples.

...It includes code for popular deep reinforcement learning techniques such as Deep Q-Networks, policy gradient methods, actor-critic architectures, and other modern RL approaches. The repository is structured so that users can easily experiment with different algorithms and training environments. Many examples demonstrate how agents learn to interact with simulated environments through trial and error using reinforcement learning principles. The codebase emphasizes clarity and modular design so that researchers can extend the implementations or use them for experimentation and benchmarking.

Diffusion for World Modeling is an experimental reinforcement learning system that trains intelligent agents inside a simulated environment generated by a diffusion-based world model. The project introduces the idea of using diffusion models, commonly used for image generation, to simulate the dynamics of an environment and predict future states based on previous observations and actions. Instead of interacting directly with a real environment, the reinforcement learning agent learns within a generative model that produces frames representing the environment. ...

...The curriculum includes a progression of topics such as foundational AI engineering skills, machine learning systems design, large language model usage, retrieval-augmented generation systems, model fine-tuning, and autonomous AI agents. It also promotes disciplined learning routines and project-based practice so learners can develop practical experience and build deployable solutions.

Amine is an Artificial Intelligence Multi-Layer Java Open Source Platform dedicated to the development of various kinds of Intelligent Systems and Agents (Knowledge-Based, Ontology-Based, Conceptual Graph -CG- Based, NLP, Reasoning and Learning, Natural Language Processing, etc.). Ontology, KB can be created and manipulated with various processes. CG theory is used as the main knowledge representation language. Amine provides two languages: PROLOG+CG which extends PROLOG with CG and Amine modules, and SYNERGY which is a visual activation/propagation based language. ...

...The repository provides a well-documented and commented implementation designed primarily for educational purposes. It allows researchers and developers to train reinforcement learning agents that can learn to play games such as Atari environments or board games. The framework is modular so that users can easily add new environments by defining the game logic and associated hyperparameters. It also includes support for distributed training, GPU acceleration, and monitoring tools for tracking learning progress.

...These demos allow users to visualize how reinforcement learning agents improve their behavior over time as they receive rewards and update their neural networks.

DeepTraffic is a deep reinforcement learning simulation designed to teach and evaluate autonomous driving algorithms in a dense highway environment. The system presents a simulated multi-lane highway where an AI-controlled vehicle must navigate traffic while maximizing speed and avoiding collisions. Participants design neural network policies that determine the vehicle’s actions, such as accelerating, decelerating, changing lanes, or maintaining speed. The project was created as part of an...

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: FOR USERS: If you want to download the latest releases, please visit: http://search.maven.org/#search|ga|1|teachingbox FOR DEVELOPERS: 1) If you use Apache Maven, just add the following dependency to your pom.xml: <dependency> <groupId>org.sf.teachingbox</groupId> <artifactId>teachingbox-core</artifactId> <version>1.2.3</version> </dependency> 2) If you want to check out the most recent source-code: git clone https://git.code.sf.net/p/teachingbox/core teachingbox-core Documentation: https://sourceforge.net/p/teachingbox/documentation/HEAD/tree/trunk/manual/

...The neural network receives input features representing the bird’s position relative to the next obstacle and determines whether the bird should flap or remain idle. Over successive generations, a genetic algorithm evolves the neural networks by selecting high-performing agents and recombining their parameters to produce improved offspring. This process allows the AI agents to gradually learn better strategies for navigating the obstacles and surviving longer in the game environment.

Pandora is an artificial intelligent web based bot written in Java. Pandora is a component based AI architecture including, database memory, XML, voice, voice rec, chat, IRC, HTTP, Wiktionary, Freebase, consciousness, language, GUI, applet, web, jsp, Android

The Mars Rover Simulator project is based on the evolutionary robotics paradigm where an artificial agent acquires its skills through the process of artificial evolution. This simulator can be useful to evolve neural network controllers for the rover

Computer System for Adaptive Intelligent Life :: seeks to create a software system that is capable of learning. The project's ultimate goal is to further the ability of software to both adapt to individual users, and to respond their needs.

Definir un entorno (medio ambiente) y a micro-organismos (gunus) que vivan en el y se desarrollen es el objeto de este proyecto.

Highly reusable and extensible Decision-Tree (Max-Gain) framework comprising of comprehensive input-processing and display functionality. Handles nominal, linear, continuous data. For preliminary description, refer - http://sushain.com/blog/archives/

Java library devoted to handle Genetic Algorithms and Classifier Systems. It has been engineered to be used into agent based simulation models and to search bounded optimal solutions in wide solution spaces. It runs on distributed clusters.