Message Schema

The message envelope is the outer wrapper containing critical metadata for routing and processing, separate from the payload. Key headers include:

• Message ID: A unique identifier for the message, enabling tracking and deduplication.
• Timestamp: The creation time, crucial for ordering and latency analysis.
• Sender/Receiver IDs: Identifiers for the originating and target agents.
• Message Type: A label (e.g., request, inform, propose) defining the communicative act or intent.
• Protocol & Version: Specifies the communication protocol (e.g., FIPA ACL, custom) and schema version for compatibility checks.
• Correlation ID: Links a response message back to its initiating request, essential for asynchronous request-response patterns.

The payload is the core content of the message, carrying the task-specific data. Its schema enforces structure and type safety.

• Structured Objects: Defined using formats like JSON Schema or Protocol Buffers, specifying required/optional fields.
• Primitive & Complex Types: Enforces data types (string, integer, float, boolean) and can define nested objects or arrays.
• Constraints & Validation: Rules for value ranges, string patterns (regex), and mandatory fields ensure data integrity before processing.
• Example: A task assignment payload might require fields task_id (string), parameters (object), and deadline (ISO 8601 timestamp).

A shared ontology provides the semantic definitions for terms used within the message payload, ensuring all agents interpret concepts identically. This prevents ambiguity.

• Domain Concepts: Defines entities (e.g., Order, Robot, SensorReading), their properties, and relationships.
• Controlled Vocabulary: Standardizes permissible values for specific fields (e.g., status: ["pending", "in_progress", "completed"]).
• Semantic Linking: Fields can reference ontology classes (e.g., "object_type": "http://ontology.org#Product"), enabling semantic reasoning by agents.

Defines the standardized format for outcomes, whether success or failure. This is critical for robust error handling and system observability.

• Success Response: Schema for payloads returned upon successful task completion.
• Error Object: A consistent structure for failures, including:
  • error_code: A machine-readable string (e.g., TASK_TIMEOUT, INVALID_PARAMETER).
  • message: Human-readable description.
  • details: Optional structured context about the failure.
• Status Propagation: Enables agents to communicate partial progress or terminal states reliably.

The schema dictates the wire format used for message serialization, the process of converting the structured message into a byte stream for transmission.

• Common Formats: Specifies the use of JSON, XML, Protocol Buffers (protobuf), Apache Avro, or MessagePack.
• Trade-offs: The choice balances human readability (JSON), efficiency and speed (protobuf, Avro), or schema evolution capabilities (Avro).
• Interoperability: A defined format ensures that agents written in different programming languages (Python, Java, Go) can seamlessly encode and decode messages.

A mechanism to manage changes to the schema over time without breaking existing agents. This is essential for long-lived systems.

• Version Identifier: A version number or hash included in the message envelope or schema URL.
• Compatibility Rules: Defines whether changes are backward compatible (old clients can read new messages) or forward compatible (new clients can read old messages).
• Deprecation Policies: Formal processes for phasing out old fields or message types, giving agent developers time to migrate.
• Schema Registry: Often used in conjunction with formats like Avro or Protobuf to centrally store and serve schema versions.

An ACL is a formal language that defines the syntax, semantics, and pragmatics of messages between agents. While a Message Schema defines what data is in a message, an ACL defines the communicative intent (e.g., inform, request, propose). The most prominent standard is FIPA ACL, which provides a library of performative verbs and a formal semantics for agent dialogues.

An MEP is a template that defines the sequence and flow of messages between parties. It dictates the interaction model that uses the structured messages defined by a schema. Common patterns include:

• Request-Response: A single request expects a single correlated reply.
• Publish-Subscribe (Pub/Sub): Publishers send messages to topics; subscribers receive messages from topics they are interested in.
• One-Way: A fire-and-forget message with no expected response.

MOM is the software infrastructure that enables asynchronous, reliable message passing between distributed components. It implements patterns like queuing and pub/sub, providing the "plumbing" through which schematized messages flow. Key components include:

• Message Brokers (e.g., RabbitMQ, Apache Kafka): Intermediaries that route and transform messages.
• Message Queues: FIFO buffers for decoupled communication.
• Protocols like AMQP and MQTT define the wire format for this middleware.

Serialization is the process of converting a structured message object (defined by its schema) into a byte stream for transmission or storage. The schema dictates the contract for serialization and deserialization. Common formats include:

• JSON: Human-readable, widely supported.
• Protocol Buffers (Protobuf): Binary, efficient, with strong schema enforcement.
• Apache Avro: Binary, with the schema embedded in the message. Choice impacts performance, payload size, and interoperability.

An envelope is a wrapper structure that contains the core message payload (which conforms to the Message Schema) along with essential metadata for handling the message. Typical envelope headers include:

• Routing information (e.g., to, from, message-id).
• Security tokens for authentication/authorization.
• Tracing identifiers for observability (e.g., trace-id).
• Timestamps and priority flags. This separates application data from system-level concerns.

These are two high-level coordination patterns that dictate how messages flow between agents to achieve a goal.

• Choreography: Control logic is distributed. Each agent knows when to act based on messages it receives from others, leading to decentralized control. It relies heavily on defined schemas and event-driven communication.
• Orchestration: A central orchestrator agent directs the workflow. It sends requests (using schematized messages) to other agents, collects responses, and manages the overall sequence and error handling.