NetHack
16 papers with code • 0 benchmarks • 0 datasets
Mean in-game score over 1000 episodes with random seeds not seen during training. See https://arxiv.org/abs/2006.13760 (Section 2.4 Evaluation Protocol) for details.
Benchmarks
These leaderboards are used to track progress in NetHack
Libraries
Use these libraries to find NetHack models and implementations
Most implemented papers
Katakomba: Tools and Benchmarks for Data-Driven NetHack
NetHack is known as the frontier of reinforcement learning research where learning-based methods still need to catch up to rule-based solutions.
LuckyMera: a Modular AI Framework for Building Hybrid NetHack Agents
pervasive-ai-lab/luckymera
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In the last few decades we have witnessed a significant development in Artificial Intelligence (AI) thanks to the availability of a variety of testbeds, mostly based on simulated environments and video games.
Motif: Intrinsic Motivation from Artificial Intelligence Feedback
Exploring rich environments and evaluating one's actions without prior knowledge is immensely challenging.
diff History for Neural Language Agents
On NetHack, an unsolved video game that requires long-horizon reasoning for decision-making, LMs tuned with diff history match state-of-the-art performance for neural agents while needing 1800x fewer training examples compared to prior work.
Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning
Either they are too slow for meaningful research to be performed without enormous computational resources, like Crafter, NetHack and Minecraft, or they are not complex enough to pose a significant challenge, like Minigrid and Procgen.
Playing NetHack with LLMs: Potential & Limitations as Zero-Shot Agents
In contrast, agents tested in dynamic robot environments face limitations due to simplistic environments with only a few objects and interactions.
