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Skip to Search Results- 19Reinforcement learning
- 3Machine learning
- 2Non-player character
- 2Robotics
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- 2Sarsa
- 1Bastani, Meysam
- 1Cutumisu, Maria
- 1Gendron-Bellemare, Marc
- 1Hao, Yongchang
- 1Jeya Veeraiah, Vivek Veeriah
- 1Mahmood, Ashique
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Fall 2021
A common scientific challenge for putting a reinforcement learning agent into practice is how to improve sample efficiency as much as possible with limited computational or memory resources. Such available physical resources may vary in different applications. My thesis introduces some approaches...
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Fall 2017
Model-free off-policy temporal-difference (TD) algorithms form a powerful component of scalable predictive knowledge representation due to their ability to learn numerous counter- factual predictions in a computationally scalable manner. In this dissertation, we address and overcome two...
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Spring 2016
In model-based reinforcement learning a model is learned which is then used to find good actions. What model to learn? We investigate these questions in the context of two different approaches to model-based reinforcement learning. We also investigate how one should learn and plan when the reward...
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Spring 2014
Each patient with Type-1 diabetes must decide how much insulin to inject before each meal to maintain an acceptable level of blood glucose. The actual injection dose is based on a formula that takes current blood glucose level and the meal size into consideration. While following this insulin...
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Fall 2009
Learning and planning are two fundamental problems in artificial intelligence. The learning problem can be tackled by reinforcement learning methods, such as temporal-difference learning, which update a value function from real experience, and use function approximation to generalise across...
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Spring 2012
We study linear estimation based on perturbed data when performance is measured by a matrix norm of the expected residual error, in particular, the case in which there are many unknowns, but the “best” estimator is sparse, or has small L1-norm. We propose a Lasso-like procedure that finds the...
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Fall 2017
The idea of an amputee playing the piano with all the flair and grace of an able-handed person may seem like a futuristic fantasy. While many prosthetic limbs look lifelike, finding one that also moves naturally has proved more of a challenge for both researchers and amputees. Even though...
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Fall 2015
The control of powered prosthetic arms has been researched for over 50 years, yet prosthetic control remains an open problem, not just from a research perspective, but from a clinical perspective as well. Significant advances have been made in the manufacture of highly functional prosthetic...
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Fall 2009
Character behaviours in computer role-playing games have a significant impact on game-play, but are often difficult for story authors to implement and modify. Many computer games use custom scripts to control the behaviours of non-player characters (NPCs). Therefore, a story author must write...