OpenEnv Hackathon SF
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Updated
Mar 8, 2026 - Jupyter Notebook
OpenEnv Hackathon SF
CNN based PPO agent and LLM based GRPO agent to play SMB on openenv wrapper using Leirbag-gabrieL's gym-super-mario-bros fork
A realistic OpenEnv environment for training AI agents to perform enterprise email triage across multi-email inbox workflows, with structured actions, tool usage, and reward shaping, built for the Scaler x Meta PyTorch Hackathon.
OpenEnv-compatible agentic debugging environment inspired by real-world Power Automate 400 BadRequest errors.
AI environment for training agents to clean messy tabular data — FastAPI + Gradio, 3 difficulty tiers, multi-dimensional grading (Scaler x Meta Hackathon)
AgentWorkBench is an OpenEnv-compatible environment designed to evaluate AI agents on real-world task management including classification, prioritization, and workflow optimization with deterministic grading.
Recursive Language Model Demo
OpenEnv-compliant RL environment simulating a customer support agent workflow with 3 graded tasks
Multi-zone disaster relief AI env for Meta PyTorch OpenEnv Hackathon. 4-stage pipeline: PyTorch ZoneScorerNet -> Triage -> Planner -> Action Agent. False SOS detection, cascading failures, airlift precision.
An OpenEnv-compatible multi-agent simulation for benchmarking LLM behavior in positive-sum economies, focusing on trust dynamics and resource scarcity.
AI-powered clinical triage simulation using Manchester Triage System (MTS). OpenEnv Challenge 2026 entry with A2A protocol support.
Simulation environment for autonomous drones that recharge using dynamic wireless power beams.
Multi-zone disaster relief AI env for Meta PyTorch OpenEnv Hackathon. 4-stage pipeline: PyTorch ZoneScorerNet -> Triage -> Planner -> Action Agent. False SOS detection, cascading failures, airlift precision.
Multi Agent Reinforcement Learning Loop to make Scientific Discoveries on Mars
Real-world Email Triage RL Environment built with OpenEnv framework
High-fidelity Reinforcement Learning environment for smart grids. Features a custom DC Power Flow physics solver and real-world AT&C telemetry to train AI in power distribution and fault isolation.
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