SSubhnil
PhD candidate at Trinity College Dublin, Ireland. I work on RL, causality, latent variables and multi-agent systems.
Trinity College DublinDublin, Ireland
Pinned Repositories
BAC-DAC-gym
Bayesian Actor-Critic with Neural Networks. Developing an OpenAI Gym toolkit for Bayesian AC reinforcement learning.
Causal-Gridworld
Testing the causal implications of the wind in the gridworld environment. The wind is the confounder.
CausalBench
Official data and code for our paper Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning
CausalCuriosity-test
Causal Curiosity fork for testing in confounded environments.
CausalTransformer_exp
Causal Transformer modification for MBRL
CDL-bench
Benchmarking CDL in confounded MDP and POMDP settings
CoGen_Benchmarking
Benchmarking existing RL algorithms including model-free and model-based approaches on confounded versions of popular environments. Tests generalization and sample efficiency.
RacingCARLA
Learning Model Predictive Control (LMPC) for autonomous racing in CARLA 3D environment.
RacingLMPC
Vehicle-Dynamics-Toolkit
Some advanced tools for race car design - Steady state and transient dynamics, Tyre Data synthesis
SSubhnil's Repositories
SSubhnil/RacingCARLA
Learning Model Predictive Control (LMPC) for autonomous racing in CARLA 3D environment.
SSubhnil/BAC-DAC-gym
Bayesian Actor-Critic with Neural Networks. Developing an OpenAI Gym toolkit for Bayesian AC reinforcement learning.
SSubhnil/CoGen_Benchmarking
Benchmarking existing RL algorithms including model-free and model-based approaches on confounded versions of popular environments. Tests generalization and sample efficiency.
SSubhnil/RacingLMPC
SSubhnil/Vehicle-Dynamics-Toolkit
Some advanced tools for race car design - Steady state and transient dynamics, Tyre Data synthesis
SSubhnil/Causal-Gridworld
Testing the causal implications of the wind in the gridworld environment. The wind is the confounder.
SSubhnil/CausalBench
Official data and code for our paper Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning
SSubhnil/CausalCuriosity-test
Causal Curiosity fork for testing in confounded environments.
SSubhnil/CausalTransformer_exp
Causal Transformer modification for MBRL
SSubhnil/CDL-bench
Benchmarking CDL in confounded MDP and POMDP settings
SSubhnil/D4PG-bench
Benchmarking D4PG in confounded environements.
SSubhnil/dreamerv3-benchmod
Modifying DreamerV3 for benchmarking in confounded environments
SSubhnil/mamba-test
Meta-RL Model-Based Algorithm - Confounding tests
SSubhnil/dreamer-new
Updated version of DreamerV3 cloned from danijar/dreamerv3
SSubhnil/DT-B
Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.
SSubhnil/dv3-torch
Benchmarking DreamerV3 with Plan2Explore.
SSubhnil/FCD-bench
Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning (ICML 2024)
SSubhnil/GRADER-bench
Repository for benchmarking GRADER in confounded environments for zero and few-shot generalization.
SSubhnil/mocoda-b
Testing MoCoDA in DM Control Suite and confounded environments.
SSubhnil/mpo-bench
Baseline tests on MPO with unobserved confounders
SSubhnil/MWM-bench
Benchmarking MWM in confounded environments
SSubhnil/P2P-bench
Code accompanying paper "Plan To Predict: Learning an Uncertainty-Foreseeing Model for Model-Based Reinforcement Learning".
SSubhnil/RIA-bench
Benchmarking RIA in confounded environments for zero and few-shot generalization. Now compatible with TF2.
SSubhnil/RIA_base
RIA base version. With new Walker environment similar to DM Control Suite physics and reward function.
SSubhnil/rl2-bench
Implementation of 'RL^2: Fast Reinforcement Learning via Slow Reinforcement Learning'
SSubhnil/sac-bench
PyTorch implementation of Soft Actor-Critic (SAC) for Unobserved Confounders
SSubhnil/SAC_dmc
SAC implementation for 3D visualization of state transitions
SSubhnil/STORM-mod
Modifying STORM transformer for Causal Transformer
SSubhnil/TMCL-b
Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning (NeurIPS 2020)
SSubhnil/twm-mod
TWM modification