Optimists at Heart: Why Do We Research Game AI? (Extended Version)
Not on the map. Why?
Abstract (arXiv)
In this paper we survey the motivations behind contemporary game AI research by analysing individual publications, the researchers themselves, and the institutions that influence them. In doing so, we identify some negative effects on our field, caused both by external forces outside of our control as well as institutionalised behaviours that are easily overlooked. We suggest how we might begin to address some of these issues as a community, and reassert ourselves as the primary driving force behind the field.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 9 of its 55 references that are in the map. First posted on arXiv 17 May 2022.
Builds on
9 of 55 references.
References · 9
- 2013Playing Atari with Deep Reinforcement Learningcited by 3,211
- 2019Dota 2 with Large Scale Deep Reinforcement Learningcited by 1,084
- 2020Deep Learning for Procedural Content Generationcited by 73
- 2020The Grey Hoodie Project: Big Tobacco, Big Tech, and the threat on academic integritycited by 38
- 2020A narrowing of AI research?cited by 12
- 2021Interactive Explanations: Diagnosis and Repair of Reinforcement Learning Based Agent Behaviorscited by 8
- 2020Towards Friendly Mixed Initiative Procedural Content Generation: Three Pillars of Industrycited by 5
- 2021The Social Responsibility of Game AIcited by 3
- 2020iNNk: A Multi-Player Game to Deceive a Neural Networkcited by 2
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