Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 14 hours
Course Outline
Introduction to Multi-Agent Systems
- Overview of Multi-Agent Systems (MAS)
- Real-world applications of MAS
- Differences compared to single-agent systems
Multi-Agent System Architectures
- Centralized versus decentralized architectures
- Hybrid and layered approaches for MAS
- Development tools and frameworks (e.g., JADE, SPADE)
Agent Communication and Coordination
- Communication protocols and languages (e.g., FIPA ACL)
- Coordination techniques: planning, negotiation, and synchronization
- Emergent behavior and self-organization in MAS
Game Theory and Decision Making
- Foundations of game theory for MAS
- Cooperative versus competitive strategies
- Conflict resolution among agents
Learning in Multi-Agent Systems
- Reinforcement learning within MAS
- Dynamics of collaborative and adversarial learning
- Knowledge sharing and transfer learning among agents
Challenges and Advanced Topics
- Scalability and performance in large-scale MAS environments
- Trust and security in agent communications
- Ethical considerations in MAS development
Practical Activities
- Building a basic MAS for resource allocation
- Simulating agent communication and coordination in dynamic settings
- Deploying a MAS using frameworks like JADE
Summary and Next Steps
Requirements
- A strong grasp of artificial intelligence concepts
- Proficiency in Python programming
- Familiarity with game theory and distributed systems (recommended)
Target Audience
- AI researchers
- AI engineers
