838 search results for “reinforcement learning” in the Public website
-
Reinforcement learning
The Reinforcement Learning lab conducts research into Reinforcement Learning and Intelligent Combinatorial Algorithms.
-
2 PhD Candidates, Reinforcement Learning for Sustainable Energy
Science, Leiden Institute of Advanced Computer Science (LIACS)
-
Searching by Learning: Exploring Artificial General Intelligence on Small Board Games by Deep Reinforcement Learning
In deep reinforcement learning, searching and learning techniques are two important components. They can be used independently and in combination to deal with different problems in AI, and have achieved impressive results in game playing and robotics. These results have inspired research into artificial…
-
Andreas Sauter
Science
-
Ili Ma
Faculteit der Sociale Wetenschappen
-
Nurbolat Kenbayev
Science
-
Artificial intelligence and machine learning
Computers are capable of making incredibly accurate predictions on the basis of machine learning. In other words, these computers can learn without intervention once they have been pre-programmed by humans. At LIACS, we explore and push the borders of what a revolutionary new generation of algorithms…
-
Franz Wurm
Faculteit der Sociale Wetenschappen
-
Aske Plaat
Science
-
Artificial Intelligence & Machine Learning
Computers are capable of making incredibly accurate predictions on the basis of machine learning. In other words, these computers can learn without intervention once they have been pre-programmed by humans. At LIACS, we explore and push the borders of what a revolutionary new generation of algorithms…
-
A Brief Introduction to Reinforcement Learning
Lecture
-
Alan Kai Hassen
Science
-
Evert van Nieuwenburg
Science
-
Collaborative learning in conservatoire education: catalyst for innovation
The aim of this research project was to increase understanding of which collaborative learning approaches already exist in conservatoire education, and how implementation of collaborative learning could be supported.
-
Learning labs in conservatoire education
Music profession requires strong reflective, collaborative, creative and improvisational skills, yet prevailing one-to-one tuition in conservatoire education focuses mainly on transmission of craft skills. Examining effects of students' collaborative and experiential learning, as in learning labs, creates…
-
Zsuzsika Sjoerds
Faculteit der Sociale Wetenschappen
-
To explore the drug space smarter: Artificial intelligence in drug design for G protein-coupled receptors
Over several decades, a variety of computational methods for drug discovery have been proposed and applied in practice. With the accumulation of data and the development of machine learning methods, computational drug design methods have gradually shifted to a new paradigm, i.e. deep learning methods…
-
PNAS Paper Prize for quantum machine learning
‘We hope our paper highlights the possibilities and benefits of including artificial intelligence in quantum physics to do new discoveries.’ Vedran Dunjko of the Leiden Institute of Advanced Computer Science contributed to a paper that was published in PNAS last year and now received a Cozzarelli Prize…
-
Searching by Learning: Exploring Artificial General Intelligence on Small Board Games by Deep Reinforcement Learning
PhD defence
-
Changing minds in social anxiety: A developmental network approach to neurocognitive bias modification
Which adolescents are more at risk of developing social anxiety disorder later in life?
-
Teachers’ professional learning preferences
How do secondary school teachers’ professional learning preferences relate to teaching experience and the school context?
-
Massively collaborative machine learning
Promotor: J. N. Kok, Co-promotor: A. J. Knobbe
-
Nonverbal Learning Disorder (NLD)
-
-
Deep learning for visual understanding
With the dramatic growth of the image data on the web, there is an increasing demand of the algorithms capable of understanding the visual information automatically.
-
Sleep and learning in children
-
-
Socially Embedded AI Systems
This interdisciplinary research project explores several adaptive machine learning methods which can give insight into the interaction between human and machine. The ultimate goal is open and natural communication between humans and AI that should result in mutual trust, cooperation and coordination…
-
Flagships
In CCLS several subgroups have formed, below you can find an overview of these groups with the names of the leading researchers and a short outline of the project.
-
Collaborative learning in higher education: design, implementation and evaluation of group learning activities
The aim of this study was to provide insight into how teachers in higher education can be supported in the design, implementation and evaluation of group assignments by developing a theoretical and evidence-based framework for the design of group assignments.
-
Professional learning: what teachers want to learn
The aim of this thesis was to examine what teachers want to learn themselves. The main research question was: what, how and why teachers want to learn? And does this depend on their years of teaching experience and the school at which they work?
-
Increased striatal activity in adolescence benefits learning
Heightened activation of the striatum that adolescents show in response to reward is often associated with risk-taking and negative health consequences. This article in Nature Communications investigates a potential positive side of this heightened activation. It shows that the activity peak in late…
-
About the programme
The curriculum of this bachelor’s programme gives you an understanding of artificial intelligence and data science with a solid basis in computer science. Both artificial intelligence and data science are broad disciplines that require essential and foundational underpinnings.
-
Blended learning
The programme is also offered in a blended learning version: this is a combination of distance learning and face-to-face learning. Read more information
-
Exploring Deep Learning for Intelligent Image Retrieval
This thesis mainly focuses on cross-modal retrieval and single-modal image retrieval via deep learning methods, i.e. by using deep convolutional neural networks.
-
Learning tools
It is our goal to deliver a convenient, enjoyable, learning experience that goes beyond the basics. All of the apps are an initiative of the HANDS! Lab for Sign Languages and Deaf Studies at Leiden University, as part of the Language Socialization in Deaf Families project funded by the Leiden University…
-
Self-directed learning with mobile technology in higher education
Language learners in higher education increasingly conduct out-of-class self-directed learning facilitated by mobile technology. This project aims to explore how university students use mobile technology for their self-directed language learning and investigate factors that influence their self-directed…
-
Collaborative learning in teacher education: Intended, implemented and experienced curriculum
How is collaborative learning in teacher education designed and implemented? How do students experience those collaborative learning assignments? What aspects of the design and the implementation lead to which perceived learning outcomes?
-
Student engagement in blended learning in higher education
In what way can teachers support and enlarge student engagement in a blended learning context?
-
Faculty of Science reinforces collaboration in China
The Faculty of Science has reinforced the collaboration in China during a group trip late November. Representatives from four institutes visited ten Chinese top universities and interviewed over 130 students in PhD workshops in Beijing and Shanghai.
-
University teachers’ learning paths during technological innovation of education
To what extent are university teachers' individual learning paths influenced by their teaching experience, motivation, and conceptions of teaching and learning through educational technology?
-
Active Learning Network
The active learning network joins together everyone interested in the subject to move the theme further within Leiden University. The SALTSWAT pilot program researches the ways forward for Leiden University.
-
Activating teaching and learning
The active learning ambition is based on the idea that knowledge is more likely to ‘stick’ when students are actively engaged with their learning and research. This active student participation has implications for how we teach: less consumption of knowledge and more efficient use of contact hours.
-
Flexible learning pathways
The ambition to have flexible learning pathways is about creating possibilities to improve the content and form of students’ learning process, and to link learning to students’ needs. Students who have access to a flexible range of learning pathways can align their university career with their own personal…
-
Programme structure
The research master's specialisation Cognitive Neuroscience consists of five main parts: the general courses, the specialisation-specific courses, the elective courses, a research internship and a thesis.
-
Centre for Professional Learning
The Centre for Professional Learning (CPL) develops in-depth and challenging programmes for higher educated professionals.
-
Neurogenomics of vocal learning
How does FoxP1 affect auditory perception on a behavioural and genomic level?
-
Leiden Learning & Innovation Centre
LLInC is a major partner in the educational network of Leiden University. We coordinate innovation initiatives across the University, provide consultation, coaching and training for teachers and faculties, and advise at a central level.
-
Object-based learning in science museums
How do museum visitors interpret the authenticity of museum objects? How can we support visitors' meaningful interactions with real objects?
-
Language Learning Resource Centre
The language learning resource centre unites all language teaching professionals working at Leiden University: teachers and researchers at the LUCL, ATC, LUCAS, LIAS, and ICLON.
-
Bayesian learning: challenges, limitations and pragmatics
This dissertation is about Bayesian learning from data. How can humans and computers learn from data?
-
Centre for Professional Learning
This page is currently only available in Dutch. Click here to view this page in Dutch.