Università della Svizzera italiana

Slowness learning for curiosity-driven agents

Kompella, Varun Raj ; Schmidhuber, Jürgen (Dir.)

Thèse de doctorat : Università della Svizzera italiana, 2014 ; 2014INFO013.

In the absence of external guidance, how can a robot learn to map the many raw pixels of high-dimensional visual inputs to useful action sequences? I study methods that achieve this by making robots self-motivated (curious) to continually build compact representations of sensory inputs that encode different aspects of the changing environment. Previous curiosity-based agents acquired skills by...

Università della Svizzera italiana

Learning to reach and reaching to learn : a unified approach to path planning and reactive control through reinforcement learning

Frank, Mikhail Alexander ; Schmidhuber, Jürgen (Dir.) ; Förster, Alexander (Codir.)

Thèse de doctorat : Università della Svizzera italiana, 2014 ; 2014INFO011.

The next generation of intelligent robots will need to be able to plan reaches. Not just ballistic point to point reaches, but reaches around things such as the edge of a table, a nearby human, or any other known object in the robot’s workspace. Planning reaches may seem easy to us humans, because we do it so intuitively, but it has proven to be a challenging problem, which continues to...

Università della Svizzera italiana

On the generation of representations for reinforcement learning

Sun, Yi ; Schmidhuber, Jürgen (Dir.)

Thèse de doctorat : Università della Svizzera italiana, 2012 ; 2012INFO001.

Creating autonomous agents that learn to act from sequential interactions has long been perceived as one of the ultimate goals of Artificial Intelligence (AI). Reinforcement Learning (RL), a subfield of Machine Learning (ML), addresses important aspects of this objective. This dissertation investigates a particular problem encountered in RL called representation generation. Two related...