---
title: "Computational Complexity of Hypothesis Assembly"
authors:
  - "Dean Allemang"
  - "Michael C. Tanner"
  - "Tom Bylander"
  - "John R. Josephson"
doi: ""
url: "https://ijcai.org/proceedings/1987/225"
pdf: "https://ijcai.org/proceedings/1987/0225.pdf"
venue: "Proceedings of the Tenth International Joint Conference on Artificial Intelligence"
year: 1987
pages: "1112-1118"
track: "Reasoning"
keywords:
---

# Computational Complexity of Hypothesis Assembly

Dean Allemang, Michael C. Tanner, Tom Bylander, John R. Josephson

*Proceedings of the Tenth International Joint Conference on Artificial Intelligence*, pages 1112-1118.

## Abstract

The problem of finding a best explanation of a set of data has been a topic of much interest in Artificial Intelligence. In this paper we present an approach to this problem by hypothesis assembly. We present this approach formally so that we can examine the time complexity and correctness of the algorithms. We then examine a system implemented using this approach, which performs red blood antibody identification. We use this domain to examine the ramifications of the assumptions of the formal model in a real world situation. We also briefly compare this approach to other assembly approaches in terms of time complexity and reliance on assumptions.