ACT-R Model Builder

Purpose

This skill encodes expert knowledge for constructing computational cognitive models within the ACT-R (Adaptive Control of Thought -- Rational) architecture. It provides guidance on chunk type definition, production rule authoring, subsymbolic parameter selection with empirically validated defaults, model fitting workflows, and validation procedures. A general-purpose programmer would not know the architecture constraints, parameter defaults, or model validation standards without specialized cognitive modeling training.

When to Use This Skill

• Designing a new ACT-R model for a cognitive task (memory retrieval, decision-making, skill acquisition)
• Setting subsymbolic parameters and understanding their theoretical justification
• Structuring chunk types and production rules for a specific experimental paradigm
• Fitting an ACT-R model to behavioral data (RT, accuracy)
• Validating a model via parameter recovery, cross-validation, or qualitative predictions
• Choosing between ACT-R 7.x (Lisp) and pyactr (Python) for implementation

Research Planning Protocol

Before executing the domain-specific steps below, you MUST: