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AI Research
arXiv CS.AI·Jun 12·5 min read
WISE: A Long-Horizon Agent in Minecraft with Why-Which Reasoning
TL;DR
Existing agents in Minecraft struggle with long-horizon tasks due to performance bottlenecks from low-level controllers. WISE (Which-Why Informed Semantic Explorer) enhances these controllers with a Causal Event Graph for better memory and reasoning.
✦ Why It Matters
Engineers can leverage WISE's causal reasoning and memory enhancements to improve AI performance in complex tasks.
Key Takeaways
- Implement causal reasoning in AI for better decision-making.
- Utilize episodic memory structures to enhance task performance.
- Adopt dynamic task scheduling based on real-time observations.
- Explore multi-scale strategies for comprehensive data collection.
Full Summary
Current embodied agents in environments like Minecraft face challenges in executing long-horizon tasks, primarily due to low-level controllers that often fail during execution. WISE addresses this by integrating a Causal Event Graph, which enhances episodic memory with causal relationships that connect observations to task relevance.
This framework allows for robust recall even when viewpoints change and supports dynamic task reordering based on causal reasoning. Additionally, WISE employs an Opportunistic Task Scheduler that re-prioritizes subtasks when relevant opportunities arise.
A multi-scale progressive exploration strategy is also implemented to ensure comprehensive spatial observations for improved reasoning. Experimental results indicate that WISE achieves a notable increase in task success rates and efficiency, particularly in scenarios requiring adaptive decision-making.
These advancements suggest significant implications for developing more capable AI agents in complex environments.