E2CL

This repository contains the code for the paper "E2CL: Exploration-based Error Correction Learning for Embodied Agents"

✨ Key Highlights

• 🎯 Novel Exploration Framework: Introduces E2CL, an innovative approach that leverages exploration-induced errors and environmental feedback to enhance embodied agents' performance

• 🤖 Self-Correction Capability: Enables agents to learn from mistakes through teacher-guided and teacher-free explorations, developing robust self-correction abilities

• 🚀 Superior Performance: Demonstrates significant improvements over traditional methods in the VirtualHome environment, achieving better environment alignment and task execution