• Journal of Korea Game Society
• /
• v.13 no.6
• /
• pp.43-52
• /
• 2013

Path finder is one of the very important algorithm of artificial intelligence and is a process generally used in many game fields. Path finder requires many calculation, so it exerts enormous influences on performances. To solve this, many researches on the ways to reduce the amount of calculate operations have been made, and the typical example is A* algorithm but it has unnecessary computing process, reducing efficiency. In this paper, to reduce the amount of calculate operations such as node search with costly arithmetic operations, we proposes the weight based pre-processing A* algorithm. The simulation was materialized to measure the efficiency of the weight based pre-process A* algorithm, and the results of the experiments showed that the weight based method was approximately 1~2 times more efficient than the general methods.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.6A
• /
• pp.614-623
• /
• 2008

A very low complexity QRD-M algorithm based on adaptive search area is proposed for MIMO systems. The conventional QRD-M scheme extends each survivor paths to all constellation symbols at each layer and selects M paths of minimum path metrics. We found that performance will not be degraded even if we adaptively restrict the survivor path extension only to the neighboring points of temporary detection symbol according to the channel condition at each layer. By employing this feature, we propose a new QRD-M algorithm achieving the near MLD performance with a reduced complexity. We employ the channel gain ratio among the layers as a channel condition indicator, which does not require SNR estimation. The simulation results show that the proposed scheme effectively achieves near MLD performance while maintaining the overall average computation complexity much smaller than the conventional QRD-M algorithm.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.2
• /
• pp.212-215
• /
• 2008

In this paper, we develop the optimal path planning algorithm using the improved Dijkstra algorithm and the particle swarm optimization. To get the optimal path, at first we construct the MAKLINK on the world environment and then make a graph associated with the MAKLINK. The MAKLINK is a set of edges which consist of the convex set. Some of the edges come from the edges of the obstacles. From the graph, we obtain the Dijkstra path between the starting point and the destination point. From the optimal path, we search the improved Dijkstra path using the graph. Finally, applying the particle swarm optimization to the improved Dijkstra path, we obtain the optimal path for the mobile robot. It turns out that the proposed method has better performance than the result in [1] through the experiment.

• Journal of KIISE
• /
• v.42 no.8
• /
• pp.961-971
• /
• 2015

As a representative area-decomposed algorithm, an area-based quad-trie (AQT) has an issue of search performance. The search procedure must continue to follow the path to its end, due to the possibility of the higher priority-matching rule, even though a matching rule is encountered in a node. A leaf-pushing AQT improves the search performance of the AQT by making a single rule node exist in each search path. This paper proposes a new algorithm to further improve the search performance of the leaf-pushing AQT. The proposed algorithm implements a leaf-pushing AQT using a hash table and an on-chip Bloom filter. In the proposed algorithm, by sequentially querying the Bloom filter, the level of the rule node in the leaf-pushing AQT is identified first. After this procedure, the rule database, which is usually stored in an off-chip memory, is accessed. Simulation results show that packet classification can be performed through a single hash table access using a reasonable sized Bloom filter. The proposed algorithm is compared with existing algorithms in terms of the memory requirement and the search performance.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.4
• /
• pp.493-498
• /
• 2004

A novel approach for path planning of a polygonal robot is presented. Traditional path planners perform extensive geometric searching to find the optimal path or to prove that there is no solution. The computation required to prove that there is no solution is equivalent to exhaustive search of the motion space, which is typically very expensive. Humans seems to use a set of several different path planning strategies to analyse the situation of the obstacles in the environment, and quickly recognize whether the path-planning problem is easy to solve, hard to solve or has no solution. This human path-planning strategies have motivated the development of the presented algorithm that combines qualitative shape reasoning and exhaustive geometric searching to speed up the path planning process. It has three planning stages consisting of identification of no-solution cases based on an enclosure test, a qualitative reasoning stage, and finally a complete search algorithm in case the previous two stages cannot determine of the existence of a solution path.

• Journal of Korea Game Society
• /
• v.17 no.5
• /
• pp.123-132
• /
• 2017

The path-finding algorithm refers to an algorithm for navigating the route order from the current position to the destination in a virtual world in a game. The conventional path-finding algorithm performs graph search based on cost such as A-Star and Dijkstra. A-Star and Dijkstra require movable node and edge data in the world map, so it is difficult to apply online games with lots of map data. In this paper, we provide a Heuristic-based Genetic Algorithm Path-finding(HGAP) using Genetic Algorithm(GA). Genetic Algorithm is a path-finding algorithm applicable to game with variable environment and lots of map data. It seek solutions through mating, crossing, mutation and evolutionary operations without the map data. The proposed algorithm is based on Binary-Coded Genetic Algorithm and searches for a path by performing a heuristic operation that estimates a path to a destination to arrive at a destination more quickly.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.27 no.1
• /
• pp.117-123
• /
• 2023

There are casualties due to inundation and flooding due to intensive typhoons or heavy rains in summer. Due to such damage, the biggest disaster is flood, and in order to reduce human damage, this paper proposes a shortest distance algorithm-based pedestrian path search study using Map API. This system selects Map API through comparative analysis and provides the shortest route. The route explored is in JSON format and the data of the shelter is stored in the database. The route search system designed and implemented based on this data locates pedestrians and provides evacuation routes in case of flash floods. In addition, if the route cannot be entered while moving to the evacuation route, the current location of the pedestrian is identified, the route is re-searched, and a new route is provided. Therefore, it is believed that the pedestrian route search system proposed in this paper will prevent negligent accidents.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.219-221
• /
• 2022

In recent summer, as it is concentrated, even in mountainous areas, flooding and flooding cause casualties in pedestrian evacuation situations. To compensate for this, a system that detects the occurrence of flooding and allows pedestrians to evacuate safely is required. Therefore, in this paper, we propose a research on pedestrian path search based on the shortest distance algorithm using Map API. The pedestrian route search system outputs a map using the T Map API, selects nearby buildings as shelters, and stores data. A shelter close to the pedestrian's current location is selected, and the shortest route is output and the distance and time are provided. If there is a problem with the current route during evacuation, another shelter route is provided from the current location. Therefore, it is thought that the pedestrian route search evacuation system proposed in this paper will prevent accidents during evacuation.

• Journal of applied mathematics & informatics
• /
• v.30 no.1_2
• /
• pp.127-133
• /
• 2012

We establish the polynomial convergence of a new class of path-following methods for SDLCP whose search directions belong to the class of directions introduced by Monteiro [3]. We show that the polynomial iteration-complexity bounds of the well known algorithms for linear programming, namely the short-step path-following algorithm of Kojima et al. and Monteiro and Alder, carry over to the context of SDLCP.

• Journal of Communications and Networks
• /
• v.4 no.3
• /
• pp.246-255
• /
• 2002

Constrained minimum Steiner tree (CMST) problem is a key issue in multicast routing with quality of service (QoS) support. Bounded shortest path algorithm (BSMA) has been recognized as one of the best algorithms for the CMST problem due to its excellent cost performance. This algorithm starts with a minimumdelay tree, and then iteratively uses a
-shortest-path (KSP) algorithm to search for a better path to replace a “superedge” in the existing tree, and consequently reduces the cost of the tree. The major drawback of BSMA is its high time complexity because of the use of the KSP algorithm. For this reason, we investigate in this paper the possibility of more efficient implementations of BSMA by using different methods to locate the target path for replacing a superedge. Our experimental results indicate that our methods can significantly reduce the time complexity of BSMA without deteriorating the cost performance.