# DiscASP: A Graph-based ASP System for Finding Relevant Consistent Concepts with Applications to Conversational Socialbots

arXiv: https://arxiv.org/abs/2109.08297 · HTML: https://mlsanity.com/paper/2109.08297/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 28 references that are in the map.
- First posted on arXiv 17 Sep 2021.

## Builds on (most cited first, 8 of 8)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Learning End-to-End Goal-Oriented Dialog](https://mlsanity.com/paper/1605.07683/) (2016)
- [Conversational AI: The Science Behind the Alexa Prize](https://mlsanity.com/paper/1801.03604/) (2018)
- [Text Summarization Techniques: A Brief Survey](https://mlsanity.com/paper/1707.02268/) (2017)
- [Clingo = ASP + Control: Preliminary Report](https://mlsanity.com/paper/1405.3694/) (2014)
- [Policy-Driven Neural Response Generation for Knowledge-Grounded Dialogue Systems](https://mlsanity.com/paper/2005.12529/) (2020)
- [Knowledge-driven Natural Language Understanding of English Text and its Applications](https://mlsanity.com/paper/2101.11707/) (2021)

## Built on by (most cited first, 2 of 2)

- [CASPR: A Commonsense Reasoning-based Conversational Socialbot](https://mlsanity.com/paper/2110.05387/) (2021)
- [Explanations for Answer Set Programming](https://mlsanity.com/paper/2308.15879/) (2023)

## Abstract (arXiv)

We consider the problem of finding relevant consistent concepts in a conversational AI system, particularly, for realizing a conversational socialbot. Commonsense knowledge about various topics can be represented as an answer set program. However, to advance the conversation, we need to solve the problem of finding relevant consistent concepts, i.e., find consistent knowledge in the "neighborhood" of the current topic being discussed that can be used to advance the conversation. Traditional ASP solvers will generate the whole answer set which is stripped of all the associations between the various atoms (concepts) and thus cannot be used to find relevant consistent concepts. Similarly, goal-directed implementations of ASP will only find concepts directly relevant to a query. We present the DiscASP system that will find the partial consistent model that is relevant to a given topic in a manner similar to how a human will find it. DiscASP is based on a novel graph-based algorithm for finding stable models of an answer set program. We present the DiscASP algorithm, its implementation, and its application to developing a conversational socialbot.