Intelligent Middle-Level Game Control

Amin Babadi, Kourosh Naderi, Perttu Hämäläinen

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

4 Citations (Scopus)
208 Downloads (Pure)


We propose the concept of intelligent middle-level game control, which lies on a continuum of control abstraction levels between the following two dual opposites: 1) high-level control that translates player’s simple commands into complex actions (such as pressing Space key for jumping), and 2) low-level control which simulates real-life complexities by directly manipulating, e.g., joint rotations of the character as it is done in the runner game QWOP. We posit that various novel control abstractions can be explored using recent advances in movement intelligence of game characters. We demonstrate this through design and evaluation of a novel 2-player martial arts game prototype. In this game, each player guides a simulated humanoid character by clicking and dragging body parts. This defines the cost function for an online continuous control algorithm that executes the requested movement. Our control algorithm uses Covariance Matrix Adaptation Evolution Strategy (CMA-ES) in a rolling horizon manner with custom population seeding techniques. Our playtesting data indicates that intelligent middle-level control results in producing novel and innovative gameplay without frustrating interface complexities.
Original languageEnglish
Title of host publicationProceedings of the 2018 IEEE Conference on Computational Intelligence and Games (CIG’18)
Number of pages8
ISBN (Electronic)9781538643594
Publication statusPublished - 13 Aug 2018
MoE publication typeA4 Conference publication
EventIEEE Conference on Computational Intelligence and Games - Maastricht University, Maastricht, Netherlands
Duration: 14 Aug 201817 Aug 2018
Conference number: 14


ConferenceIEEE Conference on Computational Intelligence and Games
Abbreviated titleCIG


  • Continuous control
  • Game control
  • Multi-agent systems
  • Online optimization
  • Physically-based simulation


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