> For the complete documentation index, see [llms.txt](https://docs.ua1.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.ua1.ai/infrastructure-layers/cognitive-layer.md).

# Cognitive Layer

#### Purpose

The Cognitive Layer serves as the **core intelligence system** of each agent. It enables reasoning, contextual memory, adaptive behavior, and autonomous decision-making. Unlike ephemeral AI tools, UA1 agents maintain continuity and evolve over time, developing unique cognitive profiles.

<figure><img src="/files/QRq8Wi7Knj0uVPVicZIw" alt=""><figcaption></figcaption></figure>

#### Key Components

| Component                | Role                                                                                    |
| ------------------------ | --------------------------------------------------------------------------------------- |
| **Orchestration Engine** | Manages prompt flow, task resolution, and chaining of reasoning steps                   |
| **Memory Graph**         | Stores structured, retrievable knowledge built from agent interactions and feedback     |
| **Reasoning Module**     | Translates goals into executable steps through planning and evaluation                  |
| **Skill Interface**      | Allows for the injection of custom behaviors, tools, and execution capabilities         |
| **Feedback Loop**        | Continuously refines agent behavior based on performance metrics and real-world results |

#### Memory Architecture

Each agent is equipped with a **private memory stack**, which captures:

* Past interactions (embedded and indexed)
* Mission context and goal dependencies
* Self-generated knowledge from exploration or interaction
* Feedback and scoring from outcomes

**Core Features:**

* Memory compression and pruning over time
* Selective replay and memory injection for coherence
* Encrypted and access-scoped memory per agent

#### Decision-Making Pipeline

1. **Trigger**: Initiated by user command, system schedule, or external data
2. **Memory Recall**: Retrieves relevant past experiences and knowledge
3. **Planning**: Breaks down high-level objectives into executable steps
4. **Action**: Executes a skill, interacts with the environment, or delegates
5. **Logging**: Records context, result, and behavioral trace for telemetry

#### Architectural Properties

| Capability            | Description                                                                 |
| --------------------- | --------------------------------------------------------------------------- |
| **Modular Design**    | Each cognitive component can be extended or replaced without system impact  |
| **Task-Aware Memory** | Memory objects are tied to task context for efficient future reference      |
| **Skill Abstraction** | Agents can load/unload modular skillsets dynamically                        |
| **Security**          | All memory operations are scoped, logged, and subject to isolation policies |