Simulation of corrupting using SMA
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Updated
Jul 7, 2017 - Java
Simulation of corrupting using SMA
Implementation of some Deep Reinforcement Learning algorithms and environments.
Collection of Pacman AI solutions from the UC Berkeley AI course
An anthill using JaCaMo.
University project. The main idea is to implement Pacman and ghosts as independent intelligent agents.
plugin to use genstar inside the Kepler scientific workflow
Multiagent system for transportation planning
UC-Berkely Pacman
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
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.
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.
An ontology to describe Hypermedia Multi-Agent Systems, interactions, and organizations.
Implementation of the G2RL approach in the POGEMA environment
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