TrackGen: An interactive track generator for TORCS and Speed-Dreams

Cardamone, Luigi; Lanzi, Pier Luca; Loiacono, Daniele

doi:10.1016/j.asoc.2014.11.010

Cited by 17 publications

(15 citation statements)

References 35 publications

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“…Successive iterations build on the best solutions from previous iterations until the generated result is of good quality. For example, TrackGen [4] used an evolutionary algorithm to produce race tracks for two 3D car racing games, TORCS and Speed-Dreams, ensuring that each generated track had an acceptable length and number of turns. Search-based methods are suitable when rules for generating content are difficult to define explicitly, but an evaluation function for various candidate solutions can be provided to select the most suitable ones.…”

Section: Search-based Pcgmentioning

confidence: 99%

Automatic generation of tower defense levels using PCG

Liu

et al. 2019

Proceedings of the 14th International Conference on the Foundations of Digital Games

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Tower defense is a popular subgenre of real-time strategy game requiring detailed level design and difficulty balancing to create an enjoyable player experience. Because level production and testing are both time-consuming and labor-intensive, we propose and implement a framework to automate the process. We first analyze the three main components, or "building blocks", of the popular tower defense game Kingdom Rush: Frontiers (KRF), i.e. road maps, tower locations and monster sequences. We then automatically create new building blocks in the style of the original game, utilizing techniques from Procedural Content Generation (PCG), and assemble them to create new levels. We also add a fourth block: automated testing via a Monte Carlo search algorithm, to ensure the generated content is playable. We focus on KRF because it is a popular video game in the tower defense genre, and highlights some of the challenges of designing appropriate PCG and playtesting algorithms for a commercial video game.

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Section: Search-based Pcgmentioning

confidence: 99%

Automatic generation of tower defense levels using PCG

Liu

et al. 2019

Proceedings of the 14th International Conference on the Foundations of Digital Games

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“…So far, SB-PCG proved to be successful in several game genres such as platform games [2]- [4], racing games [5]- [8], RPG games [9], strategy games [10], and others [11], [12].…”

Section: Related Workmentioning

confidence: 99%

“…Each user was asked to play a match against a bot with a score limit of 10 points and time limit of 10 minutes. During the match, the player can use either a red or a blue weapons 8 ; human player starts with the blue weapon, while the bot starts with the red one; during the match, the player can switch the weapon anytime; as soon as the player switches the weapon, the bot does the same, so that the player and the bot are never using the same weapon.…”

Section: User Studymentioning

confidence: 99%

Procedural weapons generation for unreal tournament III

Gravina

Loiacono

2015

2015 IEEE Games Entertainment Media Conference (GEM)

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Abstract-Design a set of weapons for a competitive first person shooter (FPS) is not an easy task: it involves several challenges, such as balancing, diversity, and novelty. In this paper, we combine procedural content generation and evolutionary computation to solve this complex task. In particular, we introduce a novel approach to procedurally generate weapons for Unreal Tournament III, a popular commercial FPS. In our approach, each weapon is represented as a parameters vector and evaluated based on game statistics. We tested our approach on three different application scenarios that represents three typical design problems: (i) create a balanced set of weapons, (ii) improve a given weapon with the least possible changes, and (iii) create a set of weapons with some specific design goals. Finally, we also performed a preliminary user study to validate our work. Our results are promising and suggest that the proposed approach might be successfully used to support the weapon design process.

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“…Later, Risi et al [19] developed a Facebook game, Petalz 3 , that applies interactive evolution to breed procedurally generated flowers. Finally, Cardamone et al [20] introduced TrackGen, a web service that exploits interactive evolution for the procedural generation of tracks for a racing game.…”

Section: Related Workmentioning

confidence: 99%

Volcano: An interactive sword generator

Pirovano

Mainetti

Loiacono

2015

2015 IEEE Games Entertainment Media Conference (GEM)

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Abstract-In this work, we introduce Volcano, a tool for the procedural generation of 3D models of swords. Unlike common procedural content generation tools, it exploits interactive evolution to reduce as much as possible the effort of the users during the generation process. Indeed, Volcano allows to forge the desired type of swords through a rather simple visual exploration of the design space. The 3D models generated with the tool can be directly used as game assets or further developed with a standard modeling software. A prototype of Volcano was tested by 30 users, including both students and game developers. The feedbacks received are very positive: tools like Volcano might be useful both for players, to create user contents, and for developers, to speed-up the design of game contents.

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TrackGen: An interactive track generator for TORCS and Speed-Dreams

Cited by 17 publications

References 35 publications

Automatic generation of tower defense levels using PCG

Automatic generation of tower defense levels using PCG

Procedural weapons generation for unreal tournament III

Volcano: An interactive sword generator

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