Simulation of corrupting using SMA

Implementation of some Deep Reinforcement Learning algorithms and environments.

Provides the package installation of JaCaMo CLI for Debian, Ubuntu, and derivatives.

Collection of Pacman AI solutions from the UC Berkeley AI course

An anthill using JaCaMo.

plugin to use genstar inside the Kepler scientific workflow

Multi-agent system Programming Tasks 2022

Tristam stands for Training Intelligent Sequencer Tool for Adaptative Music.

Aplicación desarrollada con multiagentes, donde tenemos un agente grupo de juego que gestiona las partidas y un agente jugador barquitos que es el que sabe todas las reglas del juego de los barquitos para poder jugar correctamente.

スクランブル交差点の歩行者シミュレーション

Implementation of the G2RL approach in the POGEMA environment

An ontology to describe Hypermedia Multi-Agent Systems, interactions, and organizations.

Multiagent system for transportation planning

UC-Berkely Pacman

Imagine a personal assistant in your pocket 📱 that handles your emails 📧, schedule 📅, and to-do lists ✅—all through Telegram. That's what this Telegram AI agent does! 🤖✨

This Python tool employs multi-agent routing to efficiently handle diverse tasks: one agent generates QR codes, while another retrieves and processes data from a CSV file. Depending on the user's query, the appropriate agent is dynamically selected to provide accurate responses or actions.

Implementation of projects 0,1,2,3 of Berkeley's AI course

Homework and implementation of course CS188.

Explore foundational AI concepts through the Pac-Man projects, designed for UC Berkeley's CS 188 course. Implement search algorithms, multi-agent strategies, and reinforcement learning techniques in Python, emphasizing real-world applications. Engage in the Eutopia Pac-Man contest for a multiplayer capture-the-flag challenge