---
title: "Dynamic Conflict Resolution in a Connectionist Rule-Based System"
authors:
  - "Clayton McMillan"
  - "Michael Mozer"
  - "Paul Smolensky"
doi: ""
url: "https://ijcai.org/proceedings/1993/189"
pdf: "https://ijcai.org/proceedings/1993/0189.pdf"
venue: "Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence"
year: 1993
pages: "1366-1372"
track: "Neural Networks"
keywords:
---

# Dynamic Conflict Resolution in a Connectionist Rule-Based System

Clayton McMillan, Michael Mozer, Paul Smolensky

*Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence*, pages 1366-1372.

## Abstract

In performing higher level cognitive tasks in a connectionist network, we have argued that it is useful to incorporate symbol processing formalisms and mechanisms directly into the network architecture. We have previously described a neural network, RuleNet [McMillan et al., 1992] that maps strings of input symbols to strings of output symbOls. RuleNet discovers a functional categorization of the input symbols, as well as a compact set of symbolic rules that operate on these categories to generate the output strings. The integration of subsymbolic categorization and symbolic rule following in a single system yields a variety of important consequences. This paper explores one consequence in detail, namely a novel way in which RuleNet performs conflict resolution among rules: When a conflict arises, RuleNet exploits the varying category membership strengths of input symbols to select a rule. This dynamic, content-based conflict resolution technique contrasts with traditional, broad heuristic techniques such as selection of the most specific or least recently used rule. RuleNet also has the ability to learn a priority ranking of rules, and this ranking can interact with the category-strength selection technique in a uniform quantitative framework. This uniform framework-the combination of evidence in a connectionist system-is a powerful and elegant approach to conflict resolution.