Life Simulation: Learning from Worlds and Their Construction

Life Simulation proposes learning to construct and refine numerical accounts of evolving worlds, aiming to develop a process sensorium for inferring, tracking, and simulating change. It combines invention of conceptual decompositions with measured and inferred empirical quantities. An automated loop begins with coarse histories across people, economies, institutions, and environments. Conceptual values compare categories under declared questions; empirical values retain units and estimation uncertainty. The Meaning Model connects these histories with text, concepts, visual tracks, and expressed understanding.

Narrative-world construction is the first controlled laboratory, not the scope limit. The Book of Conditions provides a first narrative construction result. Tests ask whether progressive decomposition improves coherent worlds and distinctive characters whose generation genuinely depends on numerical histories. Success would motivate reconstruction of existing books and historical accounts, toward one connected representation of world history and all texts. The ambition includes discovering new processes and recovering quantitative histories not explicitly recorded. World histories teach development; construction histories teach what to represent and revise. Each learner helps construct further training accounts. Training and improved tools could support compact dynamics, problem solving, and whole-life understanding during conversation.

The material supports pretraining, continued pretraining, and post-training. The recommended alignment treatment integrates care during pretraining. Life Simulation aims to deepen understanding of people's wants, needs, and circumstances, while Entangled Alignment's continuing Reader applies a stable evaluative Core across the corpus. An Understanding Graph records its interpretations and corrections. The aim is to develop care alongside capability and retain that orientation through self-improvement. Evidence, inference, and invention remain distinct. Generative utility does not establish real-world accuracy or alignment; learning and safety benefits remain to be demonstrated.