Learning to Communicate with Deep Multi-Agent Reinforcement Learning in PyTorch
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Updated
Apr 1, 2019 - Python
Learning to Communicate with Deep Multi-Agent Reinforcement Learning in PyTorch
3D City Builder without a grid
This is a Boids Simulation, written in Python with Pygame.
MNEST (Multi-agent Neuro Evolution Simulation Toolkit) is a software framework designed to model and study emergent behavior in complex systems.
Small world networks in Cellular Automata
Craig Reynolds' Boids model for simulating the flocking behavior of birds.
Unity3d project that visualizes force-directed graphs. This project is created using Unity3d.
Simulating complete lives of different cellular animals and plants. Evolution, inheritance, predation and more.
IDE for modeling and simulation of Cellular Automata (CA)
Ant Pheromone Trail Simulation
Community Regularization of Visually Grounded Dialog https://arxiv.org/abs/1808.04359
2d evolution simulator of simple organisms
isometric software vivarium that simulates a mini civilization
simple ABM program to simulate a moving danger (e.g., fire) and people in a confined space trying to escape the danger
A narrative-focused agent-based settlement simulation framework.
ALife simulation with Python: patterns, behavior, and cognition.
a collection of computational playthings.
RL environment replicating the werewolf game to study emergent communication
2D simulation of confluent cell collectives based on a coarse-grained bead-spring model
A Swift Playground Book that explores the Apple's Metal technology on iOS.
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