---
title: "Multiple Agents Moving Target Search"
authors:
  - "Mark Goldenberg"
  - "Alexander Kovarsky"
  - "Xiaomeng Wu"
  - "Jonathan Schaeffer"
doi: ""
url: "https://ijcai.org/proceedings/2003/264"
pdf: "https://ijcai.org/proceedings/2003/0264.pdf"
venue: "Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence"
year: 2003
pages: "1536-1537"
track: ""
keywords:
---

# Multiple Agents Moving Target Search

Mark Goldenberg, Alexander Kovarsky, Xiaomeng Wu, Jonathan Schaeffer

*Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence*, pages 1536-1537.

## Abstract

Traditional si ngle-agent search algorithms usually make simplifying assumptions (single search agent, stationary target, complete knowledge of the state, and sufficient time). There are algorithms for relaxing one or two of these constraints; in this paper we want to relax a ll four. The application domain is to have multiple search agents cooperate to pursue and capture a moving target. Agents are allowed to communicate with each other. For solving Multiple Agents Moving Target (MAMT) applications, we present a framework for specifying a family of suitable search algorithms. This paper investigates several effective approaches for solving problem instances in this domain.