Search Results for "simulations"

...The tool provides built-in functions to configure different UAV environments and supports multiple optimization objectives. It includes progress visualization to help monitor the optimization process during simulations. Users can adjust objective function weights and experiment with multiple heuristic search strategies to explore optimal solutions. This project demonstrates applications in multi-agent and multi-UAV cooperative path planning, making it useful for research and educational purposes in the field of intelligent optimization and robotics.

...The project is written to make each algorithm’s core idea easy to understand, rather than hiding the logic behind large frameworks. It keeps dependencies minimal so learners can focus on the math, implementation, and behavior of each robotics method. Visual examples and simulations help users see how algorithms move, estimate, plan, and react. PythonRobotics is especially useful for students, researchers, and engineers who want a hands-on reference for robotics fundamentals in Python.

Teeser is a java-based integration framework for engineering emergent self-organizing behavior in distributed systems. It contains tools for analysis, tuning, macroscopic probing and simulations of distributed systems. Library of tools can be extended and everybody is encouraged to provide and share its tools with the community. The main idea is to provide application designers ability to seamlessly use tools which are helpful to design self-organizing behavior. Designers can continue to use their domain tools such as favorable simulator and by pluging it into the framework can take advantage of distributed simulations in the grid, various analyzers, optimizers (particle swarm optimization, genetic algorithms, ...). ...

NOMAD is a C++ code that implements the MADS algorithm (Mesh Adaptive Direct Search) for difficult blackbox optimization problems. Such problems occur when the functions to optimize are costly computer simulations with no derivatives.

Rejection-based stochastic simulation algorithm (RSSA) is an efficient exact algorithm for doing stochastic simulation of biochemical reaction systems. RSSA improves over state of the art of stochastic simulations by avoiding and collapsing as much the number of propensity updates.

NaruGo is game AI project. Current targets are GO board game and Texas Holdem poker. It investigates Genetic programming to build game AI logic. Also EA/GP simulations for TSP, Graph layout and Prisoners Dilemma problem.

Tina's Random Number Generator Library (TRNG) is a state of the art C++ pseudo-random number generator library for sequential and parallel Monte Carlo simulations.

The Automatic Model Optimization Reference Implementation, AMORI, is a framework that integrates the modelling and the optimization processes by providing a plug-in interface for both. A genetic algorithm and Markov simulations are currently implemented.

TAROT is a easy-to-use framework for Monte Carlo simulations in python. Calculations between different kinds of randomly distributed numbers are made as easy as basic arithmetics. Tarot provides an interactive graphical interface for interpretation.

JavaGO is an Open Source Java library for the Game of GO (weiqi, baduk) analysis. Implements: base game classes, montecarlo simulations, SGF reader/writer, game variants, GTP, etc. Elegant interfaces/class design. Speed efficient w/small footprint. TDD.