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Agent Communication Protocols (ACP)

Master the fundamentals and implementation of Agent Communication Protocols (ACP) for intelligent, collaborative, and interoperable multi-agent system
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Course Duration: 10 Hours
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Agent Communication Protocols (ACP) – Online Course
 
Agent Communication Protocols (ACP) is a comprehensive, hands-on course designed to equip AI practitioners, roboticists, and multi-agent system developers with the foundational knowledge and practical skills needed to design, implement, and secure communication among autonomous agents. As multi-agent systems (MAS) continue to power domains like robotics, smart grids, autonomous vehicles, distributed AI, and edge computing, it becomes crucial to establish effective and standardized communication between these agents.
 
Agent Communication Protocols (ACP) define the rules and semantics through which intelligent agents exchange information, negotiate, cooperate, and coordinate. This course explores both theoretical models and real-world implementations of ACP, including KQML, FIPA-ACL, custom JSON-based messaging, and interaction patterns like Contract Net Protocol, auctions, and belief sharing.
 
You’ll not only learn the core concepts of ACP but also apply them by developing simulated agent interactions, distributed task-sharing models, and scalable coordination logic using popular tools and frameworks such as SPADE, JADE, LangGraph, and Python-based agent libraries.
 
What Are Agent Communication Protocols (ACP)?
 
Agent Communication Protocols are formal specifications that enable autonomous agents to interact in a meaningful, predictable, and structured way. ACPs ensure that agents can share beliefs, make commitments, resolve conflicts, negotiate, and synchronize tasks in distributed and often uncertain environments. ACPs form the backbone of agent coordination in AI-powered systems such as supply chains, smart cities, robotic swarms, and collaborative AI applications.
 
This course enables you to understand the building blocks of ACP and how to embed communication logic into multi-agent systems for interoperability, efficiency, and trustworthiness.
 
How to Use This Course
 
  1. Understand Core Theories First: Begin with foundational agent communication models, speech acts, and protocol types.
  2. Build Real Agent Dialogues: Simulate agent conversations using FIPA-compliant agents and Python libraries.
  3. Use Templates for Common Protocols: Learn reusable message structures like request-response, Contract Net, and auction protocols.
  4. Participate in Simulations: Engage in hands-on labs for robotic negotiation, distributed problem-solving, and AI collaboration.
  5. Document Interaction Patterns: Maintain a log of successful and failed agent conversations for debugging and optimization.
  6. Revisit Advanced Coordination Models: Gradually implement synchronization, role-based communication, and privacy-preserving ACP.

Course/Topic 1 - Coming Soon

  • The videos for this course are being recorded freshly and should be available in a few days. Please contact info@uplatz.com to know the exact date of the release of this course.

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Course Objectives Back to Top
By the end of this course, you will be able to:
 
  1. Understand the principles and types of Agent Communication Protocols.
  2. Implement basic to complex ACPs like request, inform, contract-net, and subscribe.
  3. Use standard formats like FIPA-ACL and KQML to structure agent messages.
  4. Design and test multi-agent interactions using frameworks like JADE and SPADE.
  5. Develop custom communication protocols in Python for scalable systems.
  6. Simulate multi-agent collaboration, negotiation, and coordination scenarios.
  7. Handle failure, timeout, and fallback communication mechanisms in agent dialogue.
  8. Secure agent communication channels using encryption and identity verification.
  9. Monitor and debug inter-agent messages using logging and message tracing tools.
  10. Apply ACPs to domains like smart mobility, robotics, finance, and distributed AI.
Course Syllabus Back to Top
Course Syllabus
 
Module 1: Introduction to Multi-Agent Systems (MAS)
  • What is a Multi-Agent System?
  • Characteristics of Intelligent Agents
  • Need for Structured Communication
Module 2: Fundamentals of Agent Communication
  • What is ACP?
  • Speech act theory and performatives
  • FIPA architecture overview
Module 3: ACP Standards and Semantics
  • FIPA-ACL: Message structure, types, and performatives
  • KQML: Knowledge Query and Manipulation Language
  • Comparison of ACP standards
Module 4: Basic Agent Interaction Patterns
  • Request-Response Pattern
  • Inform-Acknowledge
  • One-to-One vs One-to-Many Messaging
Module 5: Advanced Protocols for Coordination
  • Contract Net Protocol
  • English Auction & Dutch Auction
  • Subscribe/Notify Mechanism
  • Negotiation and Argumentation
Module 6: Implementing ACP in Python
  • Creating agent communication classes
  • Designing performatives and payload schemas
  • JSON/XML message structures
Module 7: Using SPADE and JADE
  • SPADE (Smart Python Agent Development Environment) for ACP
  • JADE (Java Agent Development Framework) overview
  • Practical exercises: Build agent dialogues
Module 8: Agent-Based Simulations
  • Simulating distributed task allocation
  • Inter-agent trust modeling
  • Failure handling and message replay
Module 9: Securing Agent Communication
  • Message integrity and confidentiality
  • Agent authentication and authorization
  • Preventing replay and spoofing attacks
Module 10: Monitoring and Observability
  • Logging and tracing agent conversations
  • Conversation IDs and message ordering
  • Analyzing message protocols with visual tools
Module 11: Real-World Applications of ACP
  • Collaborative robots (cobots)
  • Smart grid communication
  • Distributed decision-making in edge AI
  • ACP in supply chain and logistics
Module 12: Capstone Project
  • Build a multi-agent simulation using FIPA-compliant protocols
  • Demonstrate contract negotiation, failure handling, and secure messaging
Module 13: Interview Preparation
Certification Back to Top

Upon completion of this course, you will receive a Certificate of Completion from Uplatz, affirming your ability to design, implement, and analyze communication protocols in agent-based systems. The certification verifies both theoretical knowledge and applied skills in standard ACP languages like FIPA-ACL and KQML, as well as your capacity to develop secure, scalable communication flows in distributed AI ecosystems. Whether for academic research, enterprise AI solutions, or industrial multi-agent deployments, this certification signals your readiness to work with intelligent collaborative agents in real-world settings.

Career & Jobs Back to Top
The need for interoperable, collaborative AI systems is growing rapidly in robotics, logistics, smart cities, and AI automation platforms. This course positions you for cutting-edge roles such as:
  • Multi-Agent Systems Engineer
  • ACP Protocol Designer
  • Intelligent Agent Developer
  • Autonomous Robotics Developer
  • Smart Grid AI Engineer
  • AI Systems Architect (Distributed)
  • Secure Agent Communication Specialist
  • Protocol Researcher (AI Interoperability)
  • Collaborative AI Simulation Engineer
  • Edge AI Developer (MAS)
Whether in AI research labs, autonomous vehicle systems, industrial IoT, or enterprise AI, professionals skilled in ACP are crucial for designing systems where machines collaborate safely, efficiently, and intelligently.
Interview Questions Back to Top
1. What is an Agent Communication Protocol (ACP)?
ACP is a formal set of rules that governs how autonomous agents exchange information and coordinate actions within a multi-agent system.
 
2. What is the difference between FIPA-ACL and KQML?
FIPA-ACL and KQML are both standard communication languages. FIPA-ACL includes structured message formats and conversation policies, while KQML focuses on messaging performatives and knowledge exchange.
 
3. What are performatives in agent communication?
Performatives are verbs (e.g., request, inform, propose) that indicate the intention of the message sender in agent communication.
 
4. How does the Contract Net Protocol work?
It is a negotiation protocol where an agent announces a task and others bid for it. The best proposal is selected, and the task is delegated.
 
5. What is the purpose of a conversation ID in ACP?
It helps in tracking a sequence of messages in the same conversation thread to maintain context and message order.
 
6. How can ACP be implemented in Python?
By defining agent classes with performatives, message queues, and message formats (e.g., JSON), and managing interactions through predefined protocols.
 
7. What are the key security concerns in ACP?
Concerns include message tampering, spoofing, unauthorized access, and lack of encryption.
 
8. How does SPADE help in implementing ACP?
SPADE provides tools to create XMPP-based agents, manage conversations, handle messaging, and monitor agent lifecycles.
 
9. What is negotiation in ACP and how is it achieved?
Negotiation involves agents proposing, countering, and accepting offers to reach consensus, often implemented via multi-round message exchange.
 
10. In what industries are ACPs heavily used?
Industries like robotics, manufacturing, logistics, autonomous transportation, smart grids, and distributed AI use ACPs for coordination and communication.
Course Quiz Back to Top
Start Quiz
Q1. What are the payment options?
A1. We have multiple payment options: 1) Book your course on our webiste by clicking on Buy this course button on top right of this course page 2) Pay via Invoice using any credit or debit card 3) Pay to our UK or India bank account 4) If your HR or employer is making the payment, then we can send them an invoice to pay.

Q2. Will I get certificate?
A2. Yes, you will receive course completion certificate from Uplatz confirming that you have completed this course with Uplatz. Once you complete your learning please submit this for to request for your certificate https://training.uplatz.com/certificate-request.php

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A17. Our course is designed to provide you with a solid foundation in the subject and equip you with valuable skills. While the course is a significant step toward your career goals, its important to note that the job market can vary, and some positions might require additional certifications or experience. Remember that the job landscape is constantly evolving. We encourage you to continue learning and stay updated on industry trends even after completing the course. Many successful professionals combine formal education with ongoing self-improvement to excel in their careers. We are here to support you in your journey!

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c) Online Professional Network: Leverage platforms like LinkedIn, a reputable online professional network, to explore job opportunities that resonate with your skills and interests.
d) Online Job Platforms: Investigate prominent online job platforms in your region and submit applications for suitable positions considering both your prior experience and the newly acquired knowledge. e.g in UK the major job platforms are Reed, Indeed, CV library, Total Jobs, Linkedin.
While we may not offer placement services, we are here to support you in other ways. If you have any questions about the industry, job search strategies, or interview preparation, please dont hesitate to reach out. Remember that taking an active role in your job search process can lead to valuable experiences and opportunities.

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