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.
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