Estudia

• CG3- Communicate in an effective way both orally and in writing, preparing documents and presenting projects and results with English language
• CG5- Collect and select information to be able to evaluate the state of the art of a specific topic or subject
• CG6- Work in multidisciplinary teams, establishing those relationships that can help to bring out the most effective cooperation and maintain them continuously
• CB6- Possess and understand the knowledge that provides a basis or opportunity to be original in the development and/or application of ideas, often in a research context
• CB7- That students know how to apply the knowledge acquired and their ability to solve problems in new or unfamiliar environments within broader contexts related to their area of ??study
• CB10- That students have the learning skills to allow them to continue studying in a way that will mostly be self-directed or autonomous
• CE1- Programming, at an advanced level, in the languages and libraries most used in intelligent field robotics
• CE2- Analyse a problem related to intelligent autonomous systems and identify the appropriate techniques and tools to solve it
• CE3- Understand, develop, modify and effectively apply machine learning methods.
• CE5- Know, understand and be able to apply the algorithms that allow autonomous vehicles to localize themselves and navigate effectively
• CE8- Understand the mathematical foundations of intelligent robotic system algorithms

1. Intro to RL

2. Free Model Algorithms

3. Function Approximation

4. Deep Reinforcement Learning

5. Policy Search

6. Sample Efficiency

7. Advanced RL topics

• Sutton and Barton (2018). An Introduction to Reinforcement Learning, 2nd Edition. MIT Press.
• Miguel Morales (2020). Grokking Deep Reinforcement Learning. Manning.

Assessment activities:

The evaluation will take into account the work done in the laboratory (30%), a research project (50%) and a quiz (20%).

Specific criteria for the "No show" grade:
To not participate in any activity.

Single Assessment:
The students will demonstrate their practical knowledge in the laboratory and pass an exam containing all theoretical and practical contents.

Minimum requirements to pass:
A grade equal or greater than 5 must be obtained in the equation 0.2*test + 0.3*laboratories + 0.5*project

Student must send an email to the professor for organizing a meeting in which whatever issue will be addressed.

All activities will be organized with Moodle. The students and professors will communicate by email.