Personal notes about scientific and research works on "Decision-Making for Autonomous Driving"
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Updated
Dec 15, 2020
Personal notes about scientific and research works on "Decision-Making for Autonomous Driving"
Simple (but often Strong) Baselines for POMDPs in PyTorch, ICML 2022
A framework to build and solve POMDP problems. Documentation: https://h2r.github.io/pomdp-py/
Partially Observable Process Gym
Clean baseline implementation of PPO using an episodic TransformerXL memory
A Modern Probabilistic Model Checker
Adaptive Attention Span for Reinforcement Learning
Baseline implementation of recurrent PPO using truncated BPTT
Python implementation of POMDP framework and PBVI & POMCP algorithms.
Efficient Point-Based POMDP Planning by Approximating
Challenging Memory-based Deep Reinforcement Learning Agents
Solving POMDP using Recurrent networks
Modeling agents with probabilistic programs
Online Replanning in Belief Space for Partially Observable Task and Motion Problems
When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment, NeurIPS 2023 (oral)
Rich literature review and discussion on the implementation of "Hierarchical Decision-Making for Autonomous Driving"
Implementing a RL algorithm based upon a partially observable Markov decision process.
Deep Recurrent Q-Learning vs Deep Q Learning on a simple Partially Observable Markov Decision Process with Minecraft
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