Syndicated Actors

The Syndicated Actor model introduces an innovative approach to programming communicating systems, integrating elements from various existing models while addressing their key limitations. By integrating state replication, conversational concurrency, and domain-specific constructs, it offers a comprehensive framework for developing robust and flexible communicating systems.

Overview

The Syndicated Actor model is designed to simplify the programming of systems that interact with each other and the outside world. It builds on concepts from the Actor model, Tuplespace model, and publish/subscribe messaging, aiming to resolve the difficulties associated with these paradigms.

Key Concepts

1. Syndicated Actor Model:

   • Integration of Models: Combines aspects of Actors, Tuplespaces, and publish/subscribe models with Ambients-like system boundaries and Erlang-like techniques for handling partial failures.
   • Dataspaces: Special actors that route and replicate published data based on actors’ interests, providing a shared state mechanism among neighboring components.

2. Conversational Concurrency:

   • Beyond Message-Passing: Focuses on conversational frames and states rather than simple message exchanges. This model aims to encapsulate the interactions and shared state within the context of ongoing conversations.
   • Shared State: Emphasizes state synchronization over simple message passing, ensuring components have a shared understanding of the task at hand.

3. Syndicate Domain-Specific Language (DSL):

   • Language Constructs: Introduces DSL constructs to directly express syndicated actor and conversational concepts, providing ergonomic ways to manage syndicated actors and their interactions.
   • Facets: Represent conversational frames and their sub-conversations, managing state and assertions efficiently.

Detailed Components

1. Syndicated Actor Model:

   • Actors and Assertions: Actors publish parts of their internal state as assertions to peers in a reactive manner. These assertions are propagated and managed by dataspaces.
   • Dataspaces: Act as intermediaries that relay messages and replicate states, supporting mechanisms like Erlang-style links, publish/subscribe, and directory services.
   • Securing Interaction: Uses object capabilities generalized for state replication and observation, with long-lived capabilities based on Macaroons for secure delegation and authority attenuation.

2. Conversational Concurrency:

   • Framing Conversations: Tasks are framed within conversational contexts, where components share relevant domain and epistemic knowledge, along with the interests of participants.
   • Recursive Structure: Conversations can be nested within sub-conversations, each contributing to the overarching task.
   • Management of State: Each facet publishes and subscribes to assertions, maintaining a consistent conversational state even during partial failures.

3. Syndicate DSL:

   • Facets and Conversations: Each actor has facets that correspond to conversations, managing state and interactions hierarchically.
   • Assertions and Subscriptions: Facets assert their state and subscribe to relevant state changes from peers, ensuring dynamic and reactive communication.

Interaction Protocols and Data Language

1. Interaction Protocols:

   • Beyond Procedure Calls: Investigates alternative interaction patterns deserving first-class treatment in programming languages.
   • Integrated Networking: Treats all forms of IPC as networking, providing a unified approach to remote interactions.

2. Preserves Data Language:

   • Common Vocabulary: Ensures robust communication across different programming languages and network links.
   • Schemas and Syntaxes: Supports records with user-defined labels, embedded references, and atomic/compound data types, with multiple syntaxes for different purposes (e.g., human-readable, binary).

Observations

Let’s discuss the Syndicated Actors model using JP Briot’s taxonomy of programming paradigms. We can analyze it according to the three dimensions proposed by Briot: action selection, coupling flexibility, and abstraction level. Briot’s taxonomy includes procedures, objects, actors, components, services, and agents, each progressively addressing more complex interaction and abstraction needs.

Action Selection

• Syndicated Actors: The Syndicated Actor model builds on the Actor model but enhances it with eventual-consistency replication of state among actors and integrates publish/subscribe mechanisms. This allows actors to autonomously publish portions of their state and subscribe to state changes from other actors. This model supports proactive and reactive behaviors, similar to agent-oriented programming, but with a stronger emphasis on shared state and consistency.
• Comparison:
• Procedures: Static and global selection based on procedure calls.
• Objects: Dynamic selection based on object methods and late binding.
• Actors: Dynamic selection based on message passing and internal state.
• Agents: Autonomous selection based on goals and internal knowledge.
• Syndicated Actors: Combines message passing with state replication, allowing actors to dynamically adapt based on both messages and shared state changes, supporting more complex and adaptive action selection mechanisms.

Coupling Flexibility

• Syndicated Actors: The model supports flexible coupling through the use of dataspaces, which act as intermediaries for state replication and message routing. This mechanism allows for both direct and indirect coupling, supporting dynamic discovery and connection of actors based on their published state and interests.
• Comparison:
• Procedures: Tight, static coupling through direct calls.
• Objects: Encapsulated state with message passing but still relatively tight coupling.
• Actors: Loose coupling through asynchronous message passing.
• Components: Explicit architectural connectors for more flexible coupling.
• Services: Dynamic discovery and loose coupling through service-oriented architectures.
• Syndicated Actors: Enhances service-like dynamic discovery with state replication, supporting both direct interactions and publish/subscribe patterns for highly flexible and dynamic coupling.

Abstraction Level

• Syndicated Actors: This model provides a high level of abstraction by integrating concepts from actors, tuplespaces, and publish/subscribe systems. It abstracts the underlying communication mechanisms, allowing developers to focus on the logical interaction and shared state among actors. The use of a domain-specific language (DSL) further elevates the abstraction, providing constructs to manage conversational concurrency and state synchronization.
• Comparison:
• Procedures: Low-level abstraction focusing on individual operations.
• Objects: Higher abstraction through encapsulation and inheritance.
• Actors: Abstracts concurrency and distribution through message passing.
• Components: Higher abstraction for software architecture and modularity.
• Services: Abstracts interactions and dependencies through service interfaces.
• Agents: Adds cognitive abstractions like goals, plans, and beliefs.
• Syndicated Actors: Integrates high-level abstractions for state management, communication, and coordination, aligning closely with agent-oriented paradigms but with additional emphasis on shared state and publish/subscribe patterns.

Conclusion

In Briot’s taxonomy, the Syndicated Actors model represents an advanced paradigm that builds upon the strengths of actors, components, and agents while addressing their limitations. It offers sophisticated mechanisms for action selection, coupling flexibility, and abstraction level, making it suitable for complex, distributed, and interactive systems. By combining elements of state replication, publish/subscribe messaging, and conversational concurrency, Syndicated Actors provide a comprehensive framework that fits into the higher echelons of Briot’s taxonomy, closely aligning with or even extending the capabilities of multi-agent systems.

References

• https://syndicate-lang.org/about/

Page last modified: 2024-11-13 09:17:00