Summary of Asp-based Multi-shot Reasoning Via Dlv2 with Incremental Grounding, by Francesco Calimeri et al.
ASP-based Multi-shot Reasoning via DLV2 with Incremental Grounding
by Francesco Calimeri, Giovambattista Ianni, Francesco Pacenza, Simona Perri, Jessica Zangari
First submitted to arxiv on: 22 Dec 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 The paper introduces DLV2, an Artificial Intelligence tool for Knowledge Representation and Reasoning that supports Answer Set Programming (ASP), a logic-based declarative formalism widely used in academic and industrial applications. Given a logic program, DLV2 produces answer sets corresponding to problem solutions through the Ground & Solve approach. The system relies on grounding and solving steps to search for answer sets. Recent applications in stream reasoning and event processing require multi-shot reasoning capabilities, where the system remains reactive while handling rapidly changing data. This work presents an incremental reasoner evolved from DLV2 to iterated reasoning, which reuses previous computations to incrementally handle internal grounding processes and maintain a large ground program. The incremental process is transparent for users. We describe the system’s usage, applicability, and performance in practically relevant domains. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper talks about a new AI tool called DLV2 that helps us solve problems by representing knowledge and reasoning logically. It can take a problem description and find all possible solutions. The tool is useful for solving complex problems in many areas, such as stream processing and event handling. Recently, there’s been a need to be able to solve these types of problems quickly and repeatedly, while still being accurate. This paper presents an updated version of DLV2 that can do this iteratively, reusing previous work to find answers faster. The new tool is designed to be transparent and easy to use for people working with complex data. |
Keywords
» Artificial intelligence » Grounding
