Valerii's repositories
ABM
Agent based model framework to simulate collective foraging with visual private and social cues
collective_foraging
This repository contains the code to replicate and simulate a collective foraging model described in Garg et al.(2022)
FARM-GLOBE
Group Online Behavioral Experiments with FastAPI, React, and MongoDB
fast-marl
FAST iteration of MARL research ideas: A starting point for Multi-Agent Reinforcement Learning
Hierarchical-Model-Comparison
Code accompanying the paper "A Deep Learning Method for Comparing Bayesian Hierarchical Models".
meltingpot
A suite of test scenarios for multi-agent reinforcement learning.
mesa
Mesa is an open-source Python library for agent-based modeling, ideal for simulating complex systems and exploring emergent behaviors.
mesa-examples
Seminal agent based models developed using Mesa
otto
a Python package to simulate, solve and visualize the source-tracking POMDP
pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
pomdp-py
A framework to build and solve POMDP problems. Documentation: https://h2r.github.io/pomdp-py/
RN-III-Task-Explorer
Streamlit application for exploring Reward Networks III task
selfsne
Self-Supervised Noise Embeddings (Self-SNE) for dimensionality reduction and clustering
utopia
Utopia is a comprehensive modelling framework for complex and evolving systems. Docs @ https://docs.utopia-project.org — NOTE: This repository is a READ-ONLY-MIRROR of the actual development repository; please open issues and MRs there:
vagechirkov
https://vagechirkov.github.io
VectorizedMultiAgentSimulator
VMAS is a vectorized framework designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.