Ramon Fraga Pereira's repositories
AirSim-NeurIPS2019-Drone-Racing
Drone Racing @ NeurIPS 2019, built on Microsoft AirSim
apparate-jpathplan
A library for developing path-planning/search algorithms in Java
deep_rl
PyTorch implementations of Deep Reinforcement Learning algorithms (DQN, DDQN, A2C, VPG, TRPO, PPO, DDPG, TD3, SAC, ASAC, TAC, ATAC)
dreamer
Dream to Control: Learning Behaviors by Latent Imagination
dreamer-1
Dream to Control: Learning Behaviors by Latent Imagination
google-research
Google AI Research
gr1py
an enumerative reactive synthesis tool for the GR(1) fragment of LTL
jill
An efficient BDI engine for large-scale simulations
modular-rl
[ICML 2020] PyTorch Code for "One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control"
Multi-Agent-Path-Finding
Anonymous Multi-Agent Path Finding (MAPF) with Conflict-Based Search and Space-Time A*
multiagent_mujoco
Benchmark for Continuous Multi-Agent Robotic Control, based on OpenAI's Mujoco Gym environments.
OpenOCL
Open Optimal Control Library for Matlab. Trajectory Optimization and non-linear Model Predictive Control (MPC) toolbox.
pddlgym
Convert a PDDL domain into an OpenAI Gym environment.
plan2vec
Public Release of Plan2vec Implementation in pyTorch
PlanningLP
Source code of my Master's thesis "Sequencing Operator Counts with State-Space Search"
ProbabilisticPlanning
this repository contains a value iteration algorithm along with a parser for a custom file txt
pyOptimalMotionPlanning
Optimal Motion Planning package in Python
pypddl-translator
Domain and problem PDDL parser in Python3 using ply.
pyperplan-1
A lightweight STRIPS planner written in Python.
pythonpddl
This is a python PDDL parser. It is based on pddlpy [https://github.com/hfoffani/pddl-lib]
pytorch_mppi
Model Predictive Path Integral (MPPI) with approximate dynamics implemented in pytorch
rl-starter-files
RL starter files in order to immediatly train, visualize and evaluate an agent without writing any line of code
rrt-algorithms
n-dimensional RRT, RRT* (RRT-Star)
Trajectron
Code accompanying "The Trajectron: Probabilistic Multi-Agent Trajectory Modeling with Dynamic Spatiotemporal Graphs" by Boris Ivanovic and Marco Pavone.