Lyc0104

Lyc0104's Stars

• carla-simulator/rllib-integration

  Integration of RLLib and CARLA

  Language:Python6520

• agi-brain/xuance

  XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library

  Language:Python58799

• wz-ml/MetaDrive-Tutorials

  Reinforcement Learning tutorials with Metadrive: A collection of hands-on notebooks and resources to get started with reinforcement learning using the powerful MetaDrive simulation environment.

  Language:Jupyter Notebook83

• ml3705454/mapr2

  Language:Python4314

• SFU-MARS/optimized_dp

  Optimizing Dynamic Programming-Based Algorithms

  Language:Python9934

• anjianli21/prediction_based_reachability

  For the paper "Prediction-Based Reachability for Collision Avoidance in Autonomous Driving"

  Language:Python194

• jihoonerd/Human-level-control-through-deep-reinforcement-learning

  📖 Paper: Human-level control through deep reinforcement learning 🕹️

  Language:Python348

• zhexilian/On-ramp-merging-decision-making

  a learning-based decision-making algorithm for on-ramp merging

  Language:Python181

• labmlai/annotated_deep_learning_paper_implementations

  🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

  Language:Python53.9k5.6k

• thomasrantian/Confidence-aware-game-theoretic-BRT

  Language:MATLAB3

• thomasrantian/Sampling_based_motion__planning_for_humanoid_robot_arm

  Language:C++3

• peterzhukovsky/reversal_learning

  A set of matlab scripts to fit a Q-learning model to 2-choice-data (response/reward) using softmax as decision rule and log-likelihood for model fitting.

  Language:MATLAB51

• jhartford/DeepCognitiveHierarchy

  Implementation of Deep Learning for Predicting Human Strategic Behavior

  Language:Python1414

• PuYuuu/vehicle-interaction-decision-making

  The decision-making of multiple vehicles at intersection bases on level-k game and MCTS

  Language:C++6223

• robotsorcerer/ComplexBRAT

  Large robustly controlled backward reach avoid tubes.

  Language:Jupyter Notebook4

• YuhanPeng1219/Multiplayer-perimeter-defense-game

  Solve a multi agents pursuit and evasion game with backward reachable set analysis

  Language:MATLAB4

• rvl-lab-utoronto/backwards-reachability

  Using reachability analysis to determine/compute safety guarantees for control policies.

  Language:Python21

• HJReachability/helperOC

  Language:MATLAB7740

• risk-sensitive-reachability/ToolboxLS

  Clone of Ian M. Mitchell's ToolboxLS repository. (https://bitbucket.org/ian_mitchell/toolboxls)

  Language:MATLAB134

• pytorch/vision

  Datasets, Transforms and Models specific to Computer Vision

  Language:Python16k6.9k

• rohitsaikrishnan/Normal-form-games-Level-k-hierarchy-simulation

  This repostory contains that is a simulation of strategic interactions among different level-k cognitive hierarchy agents

  Language:Python31

• Farama-Foundation/HighwayEnv

  A minimalist environment for decision-making in autonomous driving

  Language:Python2.6k732

• zeonchen/DMCHM

  Lane-changing decision model based on deep Markov model and Cognitive Hierarchy model

  Language:Python151

• Walter0807/Social-CH

  [NeurIPS 2023] PyTorch Implementation of "Social Motion Prediction with Cognitive Hierarchies"

  Language:Python291

• microsoft/Alympics

  Language:Python388

• ying-wen/gr2

  Appendix and Code for Modelling Bounded Rationality in Multi-Agent Interactions by Generalized Recursive Reasoning

  Language:Python148

• daizhongxiang/R2-B2

  Code for the ICML 2020 paper: "R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games"

  Language:Python6

• maohangyu/marl_demo

  demo of multi-agent reinforcement learning algorithms, such as ATT-MADDPG (Modelling the Dynamic Joint Policy of Teammates with Attention Multi-Agent DDPG) and NCC-MARL (Neighborhood Cognition Consistent Multi-Agent Reinforcement Learning).

  Language:Python415

• oxwhirl/pymarl

  Python Multi-Agent Reinforcement Learning framework

  Language:Python1.8k380

• PKU-RL/MBOM

  Language:Python8