Essays about: "Curriculum Reinforcement Learning"
Found 5 essays containing the words Curriculum Reinforcement Learning.
-
1. “An accidental heroine” : An Investigation of Gender Representation and Gender-based Stereotypes in Swedish Digital EFL Learning Material
University essay from Stockholms universitet/Engelska institutionenAbstract : The endeavour for gender equality and against gender-based patterns (stereotypes) are topics often discussed in relation to education. Correspondingly, extensive research on textbooks used in schools around the world has been conducted, some of which include the aspect of people beyond the binary. READ MORE
-
2. Deep Reinforcement Learning on Social Environment Aware Navigation based on Maps
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Reinforcement learning (RL) has seen a fast expansion in recent years of its successful application to a range of decision-making and complex control tasks. Moreover, deep learning offers RL the opportunity to enlarge its spectrum of complex fields. READ MORE
-
3. Efficiency Comparison Between Curriculum Reinforcement Learning & Reinforcement Learning Using ML-Agents.
University essay from Blekinge Tekniska HögskolaAbstract : .... READ MORE
-
4. Simulation-Driven Machine Learning Control of a Forestry Crane Manipulator
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : A forwarder is a forestry vehicle carrying felled logs from the forest harvesting site, thereby constituting an essential part of the modern forest harvesting cycle. Successful automation efforts can increase productivity and improve operator working conditions, but despite increasing levels of automation in industry today, forwarders have remained manually operated. READ MORE
-
5. Curriculum learning for increasing the performance of a reinforcement learning agent in a static first-person shooter game
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In this thesis, we trained a reinforcement learning agent using one of the most recent policy gradient methods, proximal policy optimization, in a first-person shooter game with a static player. We investigated how curriculum learning can be used to increase performance of a reinforcement learning agent. READ MORE
