Dynamic difficulty adjustment in games by using an interactive self-organizing architecture

Ebrahimi, Adeleh; Akbarzadeh-T, Mohammad-R.

doi:10.1109/iraniancis.2014.6802557

Cited by 10 publications

(7 citation statements)

References 7 publications

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“…Evaluation of player performance can be done by comparing the player's current stats with the ideal or reference ones versus a delta time [10] (equation 1).…”

Section: Discussionmentioning

confidence: 99%

“…An example of this are the variables used in the previously mentioned Pac-Man research [10]. The number of hits on maze walls, number of keys pressed or number of direction changes must be actualized just when the corresponding action happens.…”

Section: B Data Collectionmentioning

confidence: 99%

“…A good example is given in a study using Pac-Man as a testbed. By measuring the number of hits on the maze walls, the number of keys pressed and the number of direction switches, it is possible to have an idea of what the player skills are [10]. Also the lives lost and pills collected versus time are good indicators of failure and success rate.…”

Section: A Variablesmentioning

confidence: 99%

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Exploring Dynamic Difficulty Adjustment in Videogames

Sepúlveda

Besoaín

Barriga

2019

2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)

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Videogames are nowadays one of the biggest entertainment industries in the world. Being part of this industry means competing against lots of other companies and developers, thus, making fanbases of vital importance. They are a group of clients that constantly support your company because your video games are fun. Videogames are most entertaining when the difficulty level is a good match for the player's skill, increasing the player engagement. However, not all players are equally proficient, so some kind of difficulty selection is required. In this paper, we will present Dynamic Difficulty Adjustment (DDA), a recently arising research topic, which aims to develop an automated difficulty selection mechanism that keeps the player engaged and properly challenged, neither bored nor overwhelmed. We will present some recent research addressing this issue, as well as an overview of how to implement it. Satisfactorily solving the DDA problem directly affects the player's experience when playing the game, making it of high interest to any game developer, from independent ones, to 100 billion dollar businesses, because of the potential impacts in player retention and monetization.

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“…Evaluation of player performance can be done by comparing the player's current stats with the ideal or reference ones versus a delta time [10] (equation 1).…”

Section: Discussionmentioning

confidence: 99%

Section: B Data Collectionmentioning

confidence: 99%

Section: A Variablesmentioning

confidence: 99%

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Exploring Dynamic Difficulty Adjustment in Videogames

Sepúlveda

Besoaín

Barriga

2019

2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)

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“…NEAT has since been iterated on, and has even proven to be viable to be used in realtime video games to achieve various goals such as automated content generation using cgNEAT [6], and dynamic difficulty adjustment using rtNEAT [1], in a Real-Time Strategy Game. ANNs have also been used in video games to perform a variety of tasks such as DDA, demonstrated by Li et al [7] and Ebrahimi and Akbarzadeh-T [8]. Genetic techniques have also been used in wave design for games [9].…”

Section: Related Workmentioning

confidence: 99%

A NEAT Approach to Wave Generation in Tower Defense Games

Hind

Harvey

2022

2022 International Conference on Interactive Media, Smart Systems and Emerging Technologies (IMET)

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Neural networks have shown promise when applied to video games and have proven effective at performing tasks such as dynamic difficulty adjustment (DDA). This paper explores how an evolving neural network can be applied to a tower defense game in order to generate dynamic content with the intent of increasing player engagement through the principals of flow. A NeuroEvolution of Augmenting Topologies (NEAT) neural network (NN) was trained as a wave manager to observe the current game state and generate an opposing enemy wave which best challenges the players' current tower defenses. The resulting network was compared against manually designed human waves in a blind A/B test using the Games Experience Questionnaire (GEQ) to evaluate the waves across a range of criteria. The results show that an approach like this could be viable if used for content generation purposes as no discernible difference existed in reported player experience between AI and human designed waves. However, the findings regarding subsequent increases to player engagement were inconclusive. More research is required in this field to conclusively determine if machine learning generated content can exceed the quality of content created by human designers, but the findings of this paper indicate that this approach may prove valuable to game developers in the near future by allowing them to save time and money by having AI generate content instead of requiring costly human game designer time.

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“…In another study [39], a self-organizing system (SOS) was developed, which is a group of entities that presents global system traits through local interactions while not having centralized control. This method proposes a new technique that tries to adjust the difficulty level by creating an SOS of Non-Player Characters (NPCs) that are not in the player's control.…”

Section: Self-organizing System and Artificial Neural Networkmentioning

confidence: 99%

Dynamic Difficulty Adjustment (DDA) in Computer Games: A Review

Zohaib

2018

Advances in Human-Computer Interaction

156

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Dynamic difficulty adjustment (DDA) is a method of automatically modifying a game’s features, behaviors, and scenarios in real-time, depending on the player’s skill, so that the player, when the game is very simple, does not feel bored or frustrated, when it is very difficult. The intent of the DDA is to keep the player engrossed till the end and to provide him/her with a challenging experience. In traditional games, difficulty levels increase linearly or stepwise during the course of the game. The features such as frequency, starting levels, or rates can be set only at the beginning of the game by choosing a level of difficulty. This can, however, result in a negative experience for players as they try to map a predecided learning curve. DDA attempts to solve this problem by presenting a customized solution for the gamers. This paper provides a review of the current approaches to DDA.

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Dynamic difficulty adjustment in games by using an interactive self-organizing architecture

Cited by 10 publications

References 7 publications

Exploring Dynamic Difficulty Adjustment in Videogames

Exploring Dynamic Difficulty Adjustment in Videogames

A NEAT Approach to Wave Generation in Tower Defense Games

Dynamic Difficulty Adjustment (DDA) in Computer Games: A Review

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