Knowledge representation and scalable abstract reasoning for simulated democracy in Unity

• URL: http://arxiv.org/abs/2503.05783v1
• Date: Wed, 26 Feb 2025 21:03:02 GMT
• Title: Knowledge representation and scalable abstract reasoning for simulated democracy in Unity
• Authors: Eleftheria Katsiri, Alexandros Gazis, Angelos Protopapas,
• Abstract summary: We present a novel form of scalable knowledge representation about agents in a simulated democracy, e-polis.<n>Real users respond to social challenges associated with democratic institutions.<n>At the end of the game players vote on the Smart City that results from their collective choices.
• Score: 44.99833362998488
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We present a novel form of scalable knowledge representation about agents in a simulated democracy, e-polis, where real users respond to social challenges associated with democratic institutions, structured as Smart Spatial Types, a new type of Smart Building that changes architectural form according to the philosophical doctrine of a visitor. At the end of the game players vote on the Smart City that results from their collective choices. Our approach uses deductive systems in an unusual way: by integrating a model of democracy with a model of a Smart City we are able to prove quality aspects of the simulated democracy in different urban and social settings, while adding ease and flexibility to the development. Second, we can infer and reason with abstract knowledge, which is a limitation of the Unity platform; third, our system enables real-time decision-making and adaptation of the game flow based on the player's abstract state, paving the road to explainability. Scalability is achieved by maintaining a dual-layer knowledge representation mechanism for reasoning about the simulated democracy that functions in a similar way to a two-level cache. The lower layer knows about the current state of the game by continually processing a high rate of events produced by the in-built physics engine of the Unity platform, e.g., it knows of the position of a player in space, in terms of his coordinates x,y,z as well as their choices for each challenge. The higher layer knows of easily-retrievable, user-defined abstract knowledge about current and historical states, e.g., it knows of the political doctrine of a Smart Spatial Type, a player's philosophical doctrine, and the collective philosophical doctrine of a community players with respect to current social issues.

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