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A Review of Dynamic Difficulty Adjustment Methods for Serious Games

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Optimization, Learning Algorithms and Applications (OL2A 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1754))

Abstract

Rehabilitation games can be a novel and effective approach to mental and physical rehabilitation. Since patient’s abilities differ, these types of games depend on a variety of levels of difficulty. Furthermore, it is prudent to make continuous adjustments to the difficulty in order to prevent overburdening the patient, whether on emotional or physical level. For this purpose Dynamic Difficulty Adjustment (DDA) can be a very interesting solution, as it allows for the dynamic adaptation of the game based on observed performance and on physiological data of the player. DDA has been used in games for many years as it allows tuning the game to match the player’s ideal flow, keeping high levels of motivation and challenge. This paper reviews several DDA approaches used in rehabilitation and entertainment games. We concluded that many studies use Reinforcement Learning (RL) because it requires no pre-training and can adapt the game in real time without prior knowledge.

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Acknowledgments

This work is funded by the European Regional Development Fund (ERDF) through the Regional Operational Program North 2020, within the scope of Project GreenHealth - Digital strategies in biological assets to improve well-being and promote green health, Norte-01-0145-FEDER-000042.

This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the Project Scope: UIDB/05757/2020.

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Authors and Affiliations

  1. Research Center in Digitalization and Intelligent Robotics (CeDRI), Instituto Politécnico de Bragança, Bragança, Portugal

    Júlio Castro Lopes & Rui Pedro Lopes

  2. Institute of Electronics and Informatics Engineering of Aveiro (IEETA), University of Aveiro, Aveiro, Portugal

    Rui Pedro Lopes

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  1. Júlio Castro Lopes
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  2. Rui Pedro Lopes
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Correspondence to Rui Pedro Lopes .

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Editors and Affiliations

  1. Instituto Politécnico de Bragança, Bragança, Portugal

    Ana I. Pereira

  2. University of Ljubljana, Ljubljana, Slovenia

    Andrej Košir

  3. Instituto Politécnico de Bragança, Bragança, Portugal

    Florbela P. Fernandes

  4. Instituto Politécnico de Bragança, Bragança, Portugal

    Maria F. Pacheco

  5. Instituto Politécnico de Bragança, Bragança, Portugal

    João P. Teixeira

  6. Instituto Politécnico de Bragança, Bragança, Portugal

    Rui P. Lopes

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Lopes, J.C., Lopes, R.P. (2022). A Review of Dynamic Difficulty Adjustment Methods for Serious Games. In: Pereira, A.I., Košir, A., Fernandes, F.P., Pacheco, M.F., Teixeira, J.P., Lopes, R.P. (eds) Optimization, Learning Algorithms and Applications. OL2A 2022. Communications in Computer and Information Science, vol 1754. Springer, Cham. https://doi.org/10.1007/978-3-031-23236-7_11

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  • DOI: https://doi.org/10.1007/978-3-031-23236-7_11

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