Alexander Telfar
PhD Student
School of Engineering and Computer Science
Thesis Info
Research Interests: Learning, controls, computation
Thesis Title: Model-based reinforcement learning
Supervisor: Will Browne
Thesis Title: Model-based reinforcement learning
Supervisor: Will Browne
Research Interests
I love the idea of understanding the "limits of intelligence". Our limits, the limits of computers and the limits of the universe. What is computationally/physically possible given a set of resources? Some problems are easy to solve, yet others are just fundamentally hard (like planning a road trip - travelling salesman problem, see P vs NP). I am curious about what computational (or cognitive, if you like) structures/functions are required to efficiently solve everyday problems and to understand the world around us. If an agent is given access to a memory buffer, can certain problems be solved more efficiently than others? An answer to this would hint at the advantage an animal would have in evolving (working) memory.Main.GraduateForm edit
| ResearchAreas | Learning, controls, computation |
| ThesisTitle | Model-based reinforcement learning |
| Supervisor | Will Browne |
| Qualifications | |
| Photo | I allow my photo to be used for the photo board |
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Topic revision: 07 Oct 2018, mark
Topic revision: 07 Oct 2018, mark