Cognitive Consistency Model (CCM): A Cognitive Architecture Integrating Perception, Emotion, Memory, Language, and Reasoning

This article introduces the Cognitive Consistency Model (CCM) — a unified architecture aimed at integrating five core cognitive functions: perception, emotion, memory, language, and reasoning, providing a theoretical foundation for AGI research. The project is maintained by Pool Andres Aguilar Apolinario (Akimsa3), open-sourced on GitHub, with a preprint published in June 2026 under the CC BY-NC 4.0 license. Subsequent floors will discuss its background, architecture, technical implementation, current status, and application prospects in detail.

In the fields of AI and cognitive science, building a unified architecture that can simulate human cognitive abilities is a core challenge. Traditional AI systems excel at specific tasks but struggle to flexibly integrate multiple cognitive abilities such as perception, emotion, memory, language, and reasoning. CCM was proposed in this context, aiming to create a comprehensive architecture that can uniformly handle these core functions.

The design philosophy of CCM emphasizes "consistency" (information coordination and support) between different cognitive modules, distinguishing it from traditional fragmented modular systems. It covers five core cognitive domains:

1. Perception: Processes external sensory input and converts it into internal representations;
2. Emotion: Simulates the impact of emotions on cognitive processes and decision-making;
3. Memory: Manages information storage, retrieval, and forgetting, supporting short-term and long-term memory;
4. Language: Handles natural language understanding and generation to enable information exchange;
5. Reasoning: Performs logical inference, problem-solving, and decision-making based on existing knowledge.

CCM is implemented in Python with a modular structure. The code structure includes:

• agent.py: Core logic of the agent;
• core/: Core cognitive modules;
• db/: Data storage and management;
• engines/: Various cognitive engines such as reasoning engines and language processing engines. This layered design facilitates independent development and testing of each function, and enables module collaboration through clear interfaces.

As of June 2026, CCM has released a preprint paper, disclosing its architectural design and initial implementation code. The project plans to release a complete reference implementation and additional documentation in the future. Its incremental release strategy (sharing theory via preprint first to collect feedback, then improving the implementation) is common in academic open-source projects.

The academic value of CCM lies in building a unified cognitive theoretical framework, which has potential significance for the following fields:

• Cognitive Science: Provides a computational model for understanding human cognitive mechanisms;
• AGI: Explores paths to realize human-like intelligence;
• Human-Computer Interaction: Designs interactive systems with more emotional intelligence;
• Neuroscience: Provides computational-level hypothesis verification for brain function research.

CCM is a new attempt in the field of cognitive architecture, emphasizing coordination and consistency between modules, which is closer to the working mode of the human brain. Although it is in the early stage, its theoretical framework and open-source implementation provide valuable references for researchers. With the release of subsequent versions and the accumulation of community contributions, CCM is expected to become an important tool for cognitive modeling and AGI research.