LOAISep 18, 2018

Towards Abstraction in ASP with an Application on Reasoning about Agent Policies

arXiv:1809.06638v1
Originality Synthesis-oriented
AI Analysis

This work addresses scalability issues in ASP for researchers and practitioners, but it is incremental as it builds on existing abstraction techniques.

The authors tackled the problem of large state spaces in Answer Set Programming (ASP) by introducing an automatic abstraction method that over-approximates and reduces problem size while preserving structure, and applied it to declarative policies for reactive agents with illustrative examples.

ASP programs are a convenient tool for problem solving, whereas with large problem instances the size of the state space can be prohibitive. We consider abstraction as a means of over-approximation and introduce a method to automatically abstract (possibly non-ground) ASP programs that preserves their structure, while reducing the size of the problem. One particular application case is the problem of defining declarative policies for reactive agents and reasoning about them, which we illustrate on examples.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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