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šŸ« @Umich incoming PhD (Before @SJTU)

šŸ”­ Iā€™m currently working on: šŸ¤–Embodied AI, ā›ļøReinforcement Learning, and šŸ“šNLP

šŸ“« How to reach me: telepathy, or roihn[at]umich[dot]edu

Selected works:

Towards A Holistic Landscape of Situated Theory of Mind in Large Language Models @EMNLP 2023, findings

Think, Act, and Ask: Open-World Interactive Personalized Robot Navigation @ICRA 2024

Go Beyond Imagination: Maximizing Episodic Reachability with World Models @ICML 2023, poster

Learning Exploration Policies with View-based Intrinsic Rewards @NeurIPS 2022 DRL Workshop

Smart Agent-Based Modeling: On the Use of Large Language Models in Computer Simulations preprint.

More ongoing ...

Roihn(Run) Peng's Projects

ars icon ars

An implementation of the Augmented Random Search algorithm

awesome-theory-of-mind icon awesome-theory-of-mind

Machine Theory of Mind Reading List. Built upon EMNLP Findings 2023 Paper: Towards A Holistic Landscape of Situated Theory of Mind in Large Language Models

babyai icon babyai

BabyAI platform. A testbed for training agents to understand and execute language commands.

cbet icon cbet

Change-Based Exploration Transfer

deepcubea icon deepcubea

Code for DeepCubeA, a Deep Reinforcement Learning algorithm that can learn to solve the Rubik's cube.

drone_data icon drone_data

A Cloud disk for all the data needed for drone system

sabm icon sabm

This is the offical codebase for paper: Smart Agent-Based Modeling: On the Use of Large Language Models in Computer Simulations.

stable-baselines icon stable-baselines

A fork of OpenAI Baselines, implementations of reinforcement learning algorithms

ve281 icon ve281

Course materials for VE281 SU2021, UMJI-SJTU

zhoushen_hime icon zhoushen_hime

å…Øč‡ŖåŠØč½“å®”å§¬ļ¼ˆA1高é—Ŗ/å¼•å·ę€ę‰‹ļ¼‰

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