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.

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