• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2005.05a
• /
• pp.222-231
• /
• 2005

본 논문에서는 자율 에이전트에 의해 미지의 공간을 탐사하는 실시간 그래프 탐색 알고리즘 $DFS-RTA^{\ast}$와 $DFS-PHA^{\ast}$를 제안하고 그 효율성을 비교한다. 두 알고리즘들은 모두 깊이-우선 탐색(DFS)을 기초로 하고 있으며, 직전 노드로의 빠른 후진(backtrack) 을 위해 각각 실시간 최단 경로 탐색 방법인 $RTA^{\ast}$와 $PHA^{\ast}$를 적용하는 것이 특징이다. 본 논문에서는 대표적인 3차원 온라인 게임 환경인 Unreal Tournament 게임과 지능형 캐릭터 에이전트인 KGBot를 이용한 실험을 통해 두 탐색 알고리즘의 완전성과 효율성을 분석해본다.

• Journal of Intelligence and Information Systems
• /
• v.11 no.1
• /
• pp.153-167
• /
• 2005

In this paper, we consider the problem of exploring unknown environments with a mobile robot or an autonomous character agent. Traditionally, research efforts to address the space exploration problem havefocused on the graph-based space representations and the graph search algorithms. Recently EXPLORE, one of the most efficient search algorithms, has been discovered. It traverses at most min$min(mn, d^2+m)$ edges where d is the deficiency of a edges and n is the number of edges and n is the number of vertices. In this paper, we propose DFS-RTA* and DFS-PHA*, two real-time graph search algorithms for directing an autonomous agent to explore in an unknown space. These algorithms are all built upon the simple depth-first search (DFS) like EXPLORE. However, they adopt different real-time shortest path-finding methods for fast backtracking to the latest node, RTA* and PHA*, respectively. Through some experiments using Unreal Tournament, a 3D online game environment, and KGBot, an intelligent character agent, we analyze completeness and efficiency of two algorithms.