Summary of On Policy Reuse: An Expressive Language For Representing and Executing General Policies That Call Other Policies, by Blai Bonet et al.
On Policy Reuse: An Expressive Language for Representing and Executing General Policies that Call Other Policies
by Blai Bonet, Dominik Drexler, Hector Geffner
First submitted to arxiv on: 25 Mar 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A recently introduced language for expressing and learning general policies and problem decompositions (sketches) has been extended to make policies and sketches more flexible and reusable. Specifically, three new features are added: internal memory states, indexical features, and modules that wrap up policies and sketches and allow them to call each other by passing parameters. Unlike previous work, this language also enables the selection of ground actions rather than just state transitions. The increased expressive power is demonstrated through various examples. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper introduces a new way for computers to learn and make decisions. It starts with a simple idea that lets computers solve problems in a general way. Then it adds some extra features that make this approach more powerful and flexible. Now, computers can use memory to remember things, use special features to keep track of objects, and even call other programs to get help. This new language is shown to be useful through examples. |
