Direction Oriented Pathfinding In Video Games

Cui, Xiao; Shi, Hao

doi:10.5121/ijaia.2011.2401

Cited by 19 publications

(13 citation statements)

References 3 publications

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“…In the context of games, the A* search algorithm is popular (cf. Cui and Shi, [39]). There are pros and cons to the various algorithms, the MMAS appears more flexible in settings with varying costs functions, which is determined by the human interventions in this study.…”

Section: Discussionmentioning

confidence: 99%

Interactive Ant Colony Optimization to Support Adaptation in Serious Games

Kickmeier-Rust

Holzinger²

2019

IJSG

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The success of serious games usually depends on their capabilities to engage learners and to provide them with personalized gaming and learning experiences. Therefore, it is important to equip a game, as an autonomous computer system, with a certain level of understanding about individual learning trajectories and gaming processes. AI and machine learning technologies increasingly enter the field; these technologies often fail, however, since serious games either pose highly complex problems (combining gaming and learning process) or do not provide the extensive data bases that would be required. An interesting new direction is augmenting the strength of AI technologies with human intuition and human cognition. In the present paper, we investigated performance of the MAXMIN Ant System, a combinatorial optimization algorithm, with and without human interventions to the algorithmic procedure. As a testbed, we used a clone of the Travelling Salesman problem, the Travelling Snakesman game. We found some evidence that human interventions result in superior performance than the algorithm alone. The results are discussed regarding the applicability of this pathfinding algorithm in adaptive games, exemplified by Micro Learning Space adaptation systems.

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Section: Discussionmentioning

confidence: 99%

Interactive Ant Colony Optimization to Support Adaptation in Serious Games

Kickmeier-Rust

Holzinger²

2019

IJSG

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“…It has been proved that the shortest path can be determined with proper algorithms such as the the Dijkstra algorithm or A*. It gains game people's attention because of dual capabilities of generating waypoints automatically and guaranteeing the shortest path [5,12]. Because these waypoints are generated at the vertices of obstacles without clearance, however, the planned path is too close to obstacles.…”

Section: Related Workmentioning

confidence: 98%

“…Furthermore, the movement of an NPC or a group of NPCs must be natural and realistic, and efficient planning of such path is an important task in developing games [1,2,[4][5][6][7]12,17].…”

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confidence: 99%

Efficient planning of NPC cluster movement in computer game environment

Kim

2014

Cluster Comput

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For natural group movement of non player characters (NPCs) in a computer game, an efficient planning algorithm is necessary. This paper presents a grid windowbased path planning algorithm for realistic group movement. The global path is planned in a static environment and the path is locally repaired to avoid dynamic obstacles during execution. The planning and execution processes are performed for the group, not for individual NPCs by using a 2D virtual grid window covering all the NPCs. The movement of each NPC is generated inside the grid window without complicated procedures to detect collisions. We implement and test the algorithm on a polygonal world modeling a real game background. The simulation results show that the proposed method provides natural group movement and dynamic obstacle avoidance, and the experimental result with various numbers of NPCs shows consistent performance.

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“…Although many researchers discovered that A* algorithm is ideal, Cui & Shi [19] disagreed and stated that A* could speed up by enhancing it from various perspectives. There are four suggested by Cui & Shi [19] to boost the performance of A* which are search space optimization, memory usage reduction, heuristic functions improvement, and new data structure implementation.…”

Section: Research Perspectives On the Informed Search Algorithms For Pathfinding In Gamesmentioning

confidence: 99%

“…One study by Cui & Shi [19] examined n-sided-poly-based NavMesh that is much easier to automatically produce compared to triangle-based NavMesh. They claimed that their new implementation in n-sided-poly-based NavMesh has an advantage in memory usage.…”

Section: Optimization By Changing Graph Representationmentioning

confidence: 99%

A Review on Informed Search Algorithms for Video Games Pathfinding

Kapi¹

2020

IJATCSE

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Pathfinding is a broadly applied algorithm that involved the discovery of routes between two positions by avoiding obstacles at the same time. Recently, a significant number of researchers focusing on informed search algorithms for pathfinding concerning games. However, review regarding the latest optimization in the pathfinding algorithm and its advantages still lacks in the literature. To organize this heterogeneity, this paper presents a review that focused on numerous modifications to enhance the execution of the informed search algorithm through four classified perspectives: i) modification to the graph representation, ii) enhancement of heuristic function, iii) hybrid search algorithm, and iv) new data structure. This paper also aims to discuss common challenges faced by pathfinding in video games and providing future trends for optimization. While incorporating pathfinding optimization over the past decade, this paper also aims to assist new researchers by emphasizing the potential path for further exploration.

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Direction Oriented Pathfinding In Video Games

Abstract: ABSTRACT

Cited by 19 publications

References 3 publications

Interactive Ant Colony Optimization to Support Adaptation in Serious Games

Interactive Ant Colony Optimization to Support Adaptation in Serious Games

Efficient planning of NPC cluster movement in computer game environment

A Review on Informed Search Algorithms for Video Games Pathfinding

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