PP-1: Input modules using predictive coding

Indicator from PP: use of predictive coding in input modules.

Neighborhood — ranked by edge-count

paper

framework

Predictive Processing Theory
associated_with
Theory that perception and cognition involve predictive coding; listed with indicators in Butlin et al. 2023.

cosine ≥ 0.65 · no typed edge

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

RPT-1: Input modules using algorithmic recurrenceconcept0.791
Indicator derived from RPT: use of algorithmic recurrence in input modules.
Predictive Codingframework0.782
Related framework emphasizing prediction errors; active inference extends to Markov decision processes.
RPT-2: Input modules generating organised, integrated perceptual representationsconcept0.753
Indicator: perceptual organization beyond feature extraction.
Embodied Predictive Interoception Codingframework0.745
Barrett and Simmons's neuroanatomical model of interoceptive prediction error and affect generation
How Do Protocognitive Modules At Different Scales Enablequestion0.729
Reinforcement Learning with PPOmethod0.726
Actually training Claude to comply with the conflicting objective using Proximal Policy Optimization
Scaling of Cognitive Capacity via Modularity and Feedback Loopshypothesis0.719
Processes scaling goals and stressors form positive feedback loop with modularity; both arise from and potentiate power of evolution, enabling specific predictions for cognitive capacity scaling.
MCA facilitates credit assignment because error-correcting competencies of modules reduce the need to isolate individual gene contributions.claim0.715
Claim about how MCA helps evolution deal with pleiotropy.