# Architecture Overview

MinD Robotics is designed as a layered system that separates cognition, coordination, and economic execution. This separation allows autonomous systems to scale, adapt, and interact without coupling intelligence to infrastructure.

At a high level, the architecture is composed of four core layers.

#### Cognitive Layer

The cognitive layer hosts agent logic and decision-making.

This includes:

* reasoning and planning modules
* local state and memory
* intent generation and evaluation

This layer remains agent-specific and off-chain. MinD Robotics does not impose how cognition is implemented, only how its outputs are exposed for coordination.

#### Coordination & Communication Layer

This layer enables agents to interact through the Cognitive Mesh and agent-to-agent communication channels.

It is responsible for:

* broadcasting cognitive signals and intents
* synchronizing shared state across agents
* routing action-oriented messages

The coordination layer is distributed and event-driven, allowing agents to react to changes without centralized orchestration.

#### Economic Layer

The economic layer handles autonomous value exchange between agents.

It integrates:

* x402-compatible payment flows
* micro-transaction settlement
* incentive and reward logic

This layer connects coordination with economics, allowing actions and outcomes to be directly tied to value transfer.

#### Interface Layer

The interface layer exposes MinD Robotics to external systems and humans.

It includes:

* APIs and SDKs for agent integration
* dashboards for monitoring and supervision
* connectors for bots, services, and applications

This layer ensures observability and accessibility without interfering with autonomous execution.

#### Design Principles

MinD Robotics architecture follows a few core principles:

* autonomy by default
* no centralized cognition
* clear separation between logic and settlement
* scalability through modularity

This structure allows MinD Robotics to evolve without breaking existing agents or coordination patterns.
