Pitako -- Recommending Game Design Elements in Cicero
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Abstract (arXiv)
Recommender Systems are widely and successfully applied in e-commerce. Could they be used for design? In this paper, we introduce Pitako1, a tool that applies the Recommender System concept to assist humans in creative tasks. More specifically, Pitako provides suggestions by taking games designed by humans as inputs, and recommends mechanics and dynamics as outputs. Pitako is implemented as a new system within the mixed-initiative AI-based Game Design Assistant, Cicero. This paper discusses the motivation behind the implementation of Pitako as well as its technical details and presents usage examples. We believe that Pitako can influence the use of recommender systems to help humans in their daily tasks.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 8 Jul 2019.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 2; 2024: 0; 2025: 1.
4 papers.
- 2021SuSketch: Surrogate Models of Gameplay as a Design Assistantcited by 6
- 2023A Preliminary Study on a Conceptual Game Feature Generation and Recommendation Systemcited by 6
- 2025Cardiverse: Harnessing LLMs for Novel Card Game Prototypingcited by 3
- 2023Procedural Content Generation via Knowledge Transformation (PCG-KT)cited by 2
- 2025Cardiverse: Harnessing LLMs for Novel Card Game Prototyping10 Feb 2025
- 2023A Preliminary Study on a Conceptual Game Feature Generation and Recommendation System16 Aug 2023
- 2023Procedural Content Generation via Knowledge Transformation (PCG-KT)1 May 2023
- 2021SuSketch: Surrogate Models of Gameplay as a Design Assistant22 Mar 2021