An approach towards designing problem networks in serious games

A. Parakh, P. Chundi, M. Subramaniam

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations


Integrating of subject matter onto serious games is an important problem that has been shown to impact the learning potential of serious games. A novel approach, inspired by peer-to-peer (P2P) networks, towards designing and deploying a series of problems in game scenarios is described. Given a set of problems involving a set of concepts the proposed approach automatically generates a problem network graph akin to P2P network that can then traversed by a player to collect all the concepts that are necessary to learn a topic of interest. A network traversal algorithm is described, which identifies the relevant problems and produces an efficient route through the network for learning the topic. We also describe an algorithm for mapping the problem network graph onto a game scenario by identifying groups of problems that can be placed in a single location of the game like the level of a building, arcade, or a room, physical barriers that separate, and the conditions for passing through these barriers. The proposed approach has been validated through a quantum cryptography game QuaSim and has been played by over 100 students to learn quantum cryptography basics and cryptography protocols.

Original languageEnglish (US)
Title of host publicationIEEE Conference on Games 2019, CoG 2019
PublisherIEEE Computer Society
ISBN (Electronic)9781728118840
StatePublished - Aug 2019
Event2019 IEEE Conference on Games, CoG 2019 - London, United Kingdom
Duration: Aug 20 2019Aug 23 2019

Publication series

NameIEEE Conference on Computatonal Intelligence and Games, CIG
ISSN (Print)2325-4270
ISSN (Electronic)2325-4289


Conference2019 IEEE Conference on Games, CoG 2019
Country/TerritoryUnited Kingdom


  • Game design
  • Peer-peer networks
  • Quantum computing
  • Quantum cryptography
  • Serious games

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Software


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