Workshop: Creating Autonomous Agents
O Workshop on Creating Autonomous Agents is aimed at developers, data scientists, and AI enthusiasts who want to learn how to create intelligent agents that act autonomously in different environments. During the workshop, participants will learn about the fundamental concepts of autonomous agents, AI architectures, and how to integrate machine learning to enhance agent autonomy.
1. Introduction to Autonomous Agents
- What are autonomous agents? Definitions and characteristics
- Types of agents: Reactive, proactive and social
- Areas of application of autonomous agents (robotics, simulations, games, etc.)
- Challenges in creating autonomous agents
2. Autonomous Agent Architecture
- Behavior-based architecture: BDI (Belief-Desire-Intention)
- Modeling states and transitions for decision making
- Use of decision trees and neural networks in autonomous agents
- Designing hybrid architectures for intelligent agents
3. Development of Autonomous Agents in Virtual Environments
- Creating simple agents using languages like Python and Java
- Use of frameworks and libraries for simulations (OpenAI Gym, Unity ML-Agents)
- Integration of virtual sensors and perception systems
- Implementation of controllers for autonomous actions
4. Artificial Intelligence and Machine Learning in Autonomous Agents
- Introduction to Reinforcement Learning
- Agent training in simulation environments
- Using deep learning algorithms to improve autonomy
- Creating neural networks for agents that learn from the environment
5. Development of Autonomous Agents in Robotics
- Agent integration with physical robots
- Use of real sensors and navigation systems for robotic agents
- Autonomous decision making in physical environments
- Practical examples of implementing autonomous agents in robotics
6. Autonomous Agents in Simulations and Games
- Creation of autonomous agents in virtual games
- Implementing complex behaviors in NPCs (Non-Player Characters)
- Integration of AI systems to improve interaction with players
- Multi-agent simulations and cooperation in virtual scenarios
7. Best Practices and Challenges in Creating Autonomous Agents
- Good practices in the design and development of autonomous agents
- Resource management and performance optimization
- Ethical and security challenges in implementing autonomous agents
- Testing, validation and simulation of autonomous agents
8. Future of Autonomous Agents
- Exploring recent advances in artificial intelligence for autonomous agents
- Use of collective intelligence and cooperation between agents
- Future applications in industries, transportation, healthcare and gaming
Prerequisites
- There are no prerequisites.
Who is it for?
- Professionals who want to optimize their daily work
- Developers and engineers who want to learn how to build intelligent agents
- Data scientists interested in machine learning applications for autonomy
- Artificial intelligence enthusiasts who want to explore the development of autonomous agents
- Professionals working with robotics, simulations or game development
