Search Results for "run time java" - Page 11

Proposed is an algorithm that uses computer vision, combined with a modified Rubine classifier, to allow arbitrary N-sided polygons as accepted sketches in real-time.

Neural network trainer written in Java with the ability to easily add new training algorithms and training patterns. Includes a parallel training graphical interface where you can view each trainer working in real-time in parallel.

Application of neural network to predict the future of stock exchange, aerospace ( ufo trajectory ), sound, image, noise, scientific or medical data. You need , by example, 100 days of a numeric data and the number of days to predict (by example 7 days).

This is a framework to develop Contexts and Agents and a Container to run them. The Container lets each Agent interact with the Context and other Agents. The agents are deployed in jar files and each one runs in an exclusive sandbox.

Great Malls of Fire is a crowd simulation in a shopping center-like environment. Build your mall, look at your customers shopping... Then set it on fire and then watch them run away in fear!

RoboScout is a software that simulates realistic vehicle behaviour that drives by itself and avoids obstacles in a virtual world. Every instant, the vehicle decides by itself how to modify its speed and direction according to its environment.

VKAS uses genetic programming methods to find out the relationship among a set of independent and dependent variable. It is a problem solver software which uses evolutionary computing methods. When vkas is run, it creates a population of chromosomes at random. This population is then genetically modified and next population is generated. Each population is subjected to fitness calculation and if a suitable answer chromosome is found then vkas stops and the answer is printed. If a...

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.

SNARLI (Simple Neural ARchitecture LIbrary) is a Java package containing a back-prop layer class and classes for the Self-Organizing Map and Incremental Growing Grid. The back-prop class supports sigma-pi connections and back-prop-through-time.

As of Soar 8.6.0, SGIO is no longer supported. It has been replaced by the SML interface (which is cross-platform and supports Java, Tcl, and possibly other languages by the time you read this). See http://sitemaker.umich.edu/soar for more information.

Provide a safe and simple environment for network travelling "Java Agents" or "Fish" to run and propogate. Possible uses include distributed computing, searching, and whatever else.

Jaybird is java-language based, source & xml & codebyte class inter-converting tool. You can write your Envolvable Code with it; You can make your computer write program itself; You can run program without compiling time; You can manage source as data

An object oriented framework for AI research in intelligent agents. Extensible to any information source. Graphics toolkit for visualization to view bots in real time. Extensible GUI to run bots and visualizations under common framework.

jrgp is a strong-typed Genetic Programming system, which features a graphical interface (gool) to setup and run GP-problems and a tool (fs-d) that greatly simplifies the definition of a GP-problem.

The DragonBreath Engine is a constraint solver based on local search. It features real-time computation, handling of dynamics, structural constraint satisfaction, and an easy way to include domain-specific knowledge.

Jthello is an othello (reversi) clone written in Java. It is designed to run over a network and to implement/compare different computer player (A.I.)

openai-realtime-console is a developer tool created by OpenAI that provides a web-based console for experimenting with the Realtime API. The Realtime API enables low-latency, interactive communication with language models, supporting use cases such as live conversations, real-time transcription, and interactive applications. This console serves as a reference implementation, showing how to establish WebRTC or WebSocket connections, send audio or text inputs, and receive model outputs in real time. It is built as a simple frontend that developers can run locally to test and understand how Realtime API interactions work. ...

This project aim to provide a crowd movement simulation based on primitive human behaviours and emerging behaviours for research and educational purposes. The application (front-end) is generic and can be reused.

This project is an implementation of a computational framework that addresses general-interest low-level problems such as real-time synchronization, sound communication and spatial agent mobility.

This intelligence Service uses data mining and search-engine techniques to get interesting information out of the internet. The information may be about politicians or companies e.g. and covers longer time periods to create a press review for instance.

...As an FP8 instruct-fine-tuned model, it is optimized for chat, instruction following, and compact agentic tasks while maintaining strong adherence to system prompts. Despite its small size, it delivers efficient real-time performance and can run locally on a single 8GB GPU, with further memory reductions through quantization. It supports dozens of languages across major global regions, making it well-suited for multilingual and embedded applications. The model also provides function calling, clean JSON output, and stable tool-use behavior, enabling it to serve as a small but effective agentic system.

Ministral 3 3B Base 2512 is the smallest model in the Ministral 3 family, offering a compact yet capable multimodal architecture suited for lightweight AI applications. It combines a 3.4B-parameter language model with a 0.4B vision encoder, enabling both text and image understanding in a tiny footprint. As the base pretrained model, it is not fine-tuned for instructions or reasoning, making it the ideal foundation for custom post-training, domain adaptation, or specialized downstream tasks....