Telogenesis: Goal Is All U Need
arXiv cs.AI / 3/11/2026
Ideas & Deep AnalysisModels & Research
Key Points
- The paper proposes a novel priority function for goal-conditioned systems that generates attentional targets internally based on three epistemic gaps: ignorance, surprise, and staleness.
- Validation is performed in two environments, showing that each component of the priority function is essential for effective attention allocation.
- Key findings include a metric-dependent reversal in performance favoring either coverage-based or priority-guided allocation depending on the metric and dimension of the problem.
- The system can learn decay rates per variable, enabling it to autonomously identify and adapt to environmental volatility without external supervision.
- Overall, the study demonstrates that internal epistemic gaps alone can drive adaptive, goal-oriented attention mechanisms that outperform fixed strategies and reveal latent environmental structures.
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