Summary of The Case For Developing a Foundation Model For Planning-like Tasks From Scratch, by Biplav Srivastava et al.
The Case for Developing a Foundation Model for Planning-like Tasks from Scratch
by Biplav Srivastava, Vishal Pallagani
First submitted to arxiv on: 6 Apr 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
Summary difficulty | Written by | Summary |
---|---|---|
High | Paper authors | High Difficulty Summary Read the original abstract here |
Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper explores the potential of Foundation Models (FMs) in planning-like (PL) tasks, which involve generating a series of actions to achieve intended goals. While FMs have shown promise in Automated Planning and Scheduling (APS), there is a need for a comprehensive FM designed specifically for PL tasks from scratch. The authors argue that such an FM will enable new and efficient avenues for solving PL problems. |
Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper talks about special kinds of artificial intelligence called Foundation Models. They’re super useful for planning things, like making a schedule or a to-do list. But researchers want to know if these models can also help with other tasks that involve making a series of actions to achieve a goal. The authors think that creating a new type of Foundation Model just for this kind of task could be really helpful. |