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Duration 14 hours
Course Outline
Introduction to Multi-Agent Systems
- Defining multi-agent systems and their practical applications
- The role of Agentic AI in autonomous agent interactions
- Key challenges in multi-agent coordination
Developing Agentic AI for Multi-Agent Environments
- Designing autonomous AI agents
- Strategies for agent communication and decision-making
- Creating simulation environments for multi-agent AI
Reinforcement Learning for Agentic AI
- Applying reinforcement learning to multi-agent systems
- Training autonomous agents for adaptive behaviour
- Balancing exploration and exploitation in decision-making processes
Collaboration and Competition in Multi-Agent Systems
- Cooperative strategies for AI agents
- Competitive and adversarial interactions among AI agents
- Emergent behaviours in multi-agent environments
Agentic AI in Robotics and Automation
- Multi-agent coordination in robotic systems
- Swarm intelligence and decentralised decision-making
- Case studies on robotic AI applications
Agentic AI in Game Development
- Designing AI-driven NPCs in multi-agent simulations
- Behaviour modelling for interactive AI agents
- Real-time AI decision-making in dynamic environments
Scaling Multi-Agent AI Systems
- Performance optimisation for large-scale AI interactions
- Managing agent hierarchies and role-based decision-making
- Integrating AI agents with cloud-based environments
The Future of Multi-Agent Systems with Agentic AI
- Emerging trends in autonomous AI collaboration
- Expanding multi-agent AI capabilities through deep learning
- Ethical and regulatory considerations for multi-agent AI
Summary and Next Steps
Requirements
- Prior experience in AI model development
- A solid understanding of multi-agent system concepts
- Familiarity with reinforcement learning and AI-driven automation
Target Audience
- AI researchers focusing on autonomous agent interactions
- Robotics engineers working on multi-agent coordination
- Game developers implementing AI-driven NPC behaviours
Testimonials (1)
practical exercises
