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Virtual Robot Climbing Using Reinforcement Learning, Ujjawal Garg
Virtual Robot Climbing Using Reinforcement Learning, Ujjawal Garg
Master's Projects
Reinforcement Learning (RL) is a field of Artificial Intelligence that has gained a lot of attention in recent years. In this project, RL research was used to design and train an agent to climb and navigate through an environment with slopes. We compared and evaluated the performance of two state-of-the-art reinforcement learning algorithms for locomotion related tasks, Deep Deterministic Policy Gradients (DDPG) and Trust Region Policy Optimisation (TRPO). We observed that, on an average, training with TRPO was three times faster than DDPG, and also much more stable for the locomotion control tasks that we experimented. We conducted experiments and …
Deep Visual Recommendation System, Raksha Sunil
Deep Visual Recommendation System, Raksha Sunil
Master's Projects
Recommendation system is a filtering system that predicts ratings or preferences that a user might have. Recommendation system is an evolved form of our trivial information retrieval systems. In this paper, we present a technique to solve new item cold start problem. New item cold start problem occurs when a new item is added to a shopping website like Amazon.com. There is no metadata for this item, no ratings and no reviews because it’s a new item in the system. Absence of data results in no recommendation or bad recommendations. Our approach to solve new item cold start problem requires …