From Alife Agents to a Kingdom of N Queens

TL;DR

This paper introduces a novel agent-based ALife approach to solving large-scale N-queen problems by modeling agents with reactive behaviors and evolutionary selection, demonstrating effectiveness in complex constraint satisfaction tasks.

Contribution

It presents a new distributed autonomous agent model for N-queen problems, integrating ALife concepts and evolutionary strategies for efficient problem solving.

Findings

Successfully solves large-scale N-queen problems

Demonstrates effectiveness of ALife agents in CSPs

Shows agents evolve through survival and competition

Abstract

This paper presents a new approach to solving N-queen problems, which involves a model of distributed autonomous agents with artificial life (ALife) and a method of representing N-queen constraints in an agent environment. The distributed agents locally interact with their living environment, i.e., a chessboard, and execute their reactive behaviors by applying their behavioral rules for randomized motion, least-conflict position searching, and cooperating with other agents etc. The agent-based N-queen problem solving system evolves through selection and contest according to the rule of Survival of the Fittest, in which some agents will die or be eaten if their moving strategies are less efficient than others. The experimental results have shown that this system is capable of solving large-scale N-queen problems. This paper also provides a model of ALife agents for solving general CSPs.