Mateus224 / Visual-Explanation-in-Deep-Reinforcement-LearningLinks
This project visualizes the knowledge of an agent trained by Deep Reinforcement Learning (paper will be published) using Backpropagation, Guided Backpropagation, GradCam and Guided gradCam. It shows why the agent is performing the action. Which pixels had the biggest influence on the decision of the agent.
☆18Updated 5 years ago
Alternatives and similar repositories for Visual-Explanation-in-Deep-Reinforcement-Learning
Users that are interested in Visual-Explanation-in-Deep-Reinforcement-Learning are comparing it to the libraries listed below
Sorting:
- ☆11Updated 4 years ago
- PyTorch implementation of D4PG with the SOTA IQN Critic instead of C51. Implementation includes also the extensions Munchausen RL and D2R…☆24Updated 4 years ago
- Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient - 7th ICML AutoML workshop 2020☆32Updated 4 years ago
- Multi-objective reinforcement learning for covid-19 control☆12Updated 4 years ago
- Implementation of Relational Deep Reinforcement Learning☆25Updated 5 years ago
- ☆20Updated 6 years ago
- Multi-task Multi-agent Soft Actor Critic for SMAC☆12Updated 3 years ago
- This repo is the implementation of paper ''SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learning''.☆49Updated last year
- ☆31Updated 4 years ago
- multiagent-gail working with multiagent-particle-env-v2 (which was modified by magail authors)☆12Updated 6 years ago
- Official implementation of "Graph Meta-Reinforcement Learning for TransferableAutonomous Mobility-on-Demand"☆14Updated 3 years ago
- Implementation for paper "A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning".☆59Updated last year
- [AAMAS 2023] Code for the paper "Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning"☆12Updated last year
- Our version of #Exploration: A Study of Count-Based Explorationfor Deep Reinforcement Learning for a class project☆16Updated 4 years ago
- The official repository of Decoupled Reinforcement Learning to Stabilise Intrinsically-Motivated Exploration" (AAMAS 2022)☆27Updated 3 years ago
- Negative Update Intervals in Multi-Agent Deep Reinforcement Learning☆33Updated 6 years ago
- ☆12Updated 4 years ago
- Code associated with our paper "Estimating Risk and Uncertainty in Reinforcement Learning"☆11Updated 2 years ago
- Attention-based Curiosity-driven Exploration in Deep Reinforcement Learning☆27Updated 5 years ago
- Actor-Sharer-Learner training framework for off-policy DRL algorithms☆21Updated 9 months ago
- The code for AAMAS2022 《GCS: Graph-based Coordination Strategy for Multi-Agent Reinforcement Learning》☆42Updated 3 years ago
- PDiT: Interleaving Perception and Decision-making Transformers for Deep Reinforcement Learning. AAMAS 2024 (full paper with oral presenta…☆10Updated last year
- Fully Cooperative Multi-Agent Deep Reinforcement Learning☆28Updated 5 years ago
- Implementation of Hierarchical Deep Q-Learning (Kulkarni et al., 2016)☆35Updated 6 years ago
- Collection of OpenAI parametrized action-space environments.☆66Updated 6 months ago
- ☆17Updated last year
- Experimenting with meta-learning approaches to opponent modelling in MARL. Building upon previous public implementations of MADDPG and M3…☆15Updated 3 years ago
- PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning☆50Updated 4 years ago
- This is the code repository for the paper "Zero-Sum Stochastic Stackelberg Games".☆15Updated 2 years ago
- PyTorch implementation of the Munchausen Reinforcement Learning Algorithms M-DQN and M-IQN☆45Updated 5 years ago