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Skip to Search Results- 50Artificial Intelligence
- 19Machine Learning
- 8Reinforcement Learning
- 6Deep Learning
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- 4Computing Science
- 1Akbari, Mojtaba
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- 1Ashley, Dylan R
- 1Ashrafi Asli, Seyed Arad
- 1Atrazhev, Peter
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Interrelating Prediction and Control Objectives in Episodic Actor-Critic Reinforcement Learning
DownloadFall 2020
The reinforcement learning framework provides a simple way to study computational intelligence as the interaction between an agent and an environment. The goal of an agent is to accrue as much reward as possible by intelligently choosing actions given states. This problem of finding a policy that...
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Spring 2015
Computer-based interactive environments present a compelling platform for research in Artificial Intelligence. Using games as its domains, this work has traditionally focused on building AI agents that can play games well (e.g., Checkers, Go, or StarCraft). In more recent years, a parallel line...
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Fall 2014
Designing competitive Artificial Intelligence (AI) systems for Real-Time Strategy (RTS) games often requires a large amount of expert knowledge (resulting in hard-coded rules for the AI system to follow). However, aspects of an RTS agent can be learned from human replay data. In this thesis, we...
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Spring 2016
Algorithmic decipherment is a prime example of a truly unsupervised problem. This thesis presents several algorithms developed for the purpose of decrypting unknown alphabetic scripts representing unknown languages. We assume that symbols in scripts which contain no more than a few dozen unique...
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Application of Artificial Intelligence in Hip Ultrasound and its Performance in Detecting Developmental Dysplasia of the Hip
DownloadSpring 2022
Developmental Dysplasia of Hip (DDH) which represents a wide range of abnormalities from acetabular dysplasia to fixed dislocation, is mainly defined by a loss of conformity between the femoral head and the acetabulum and it can lead to structural instability and osteoarthritis. The diagnosis of...
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Developing Hybrid Artificial Intelligence Model for Construction Labour Productivity Prediction and Optimization
DownloadFall 2021
Construction labour productivity (CLP) is considered one of the most important parameters affecting the performance of construction projects. Therefore, modeling CLP is a crucial step in construction projects. Accurate prediction of CLP helps in effective planning, cost estimating, and...
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Spring 2021
Learning about many things can provide numerous benefits to a reinforcement learning system. For example, learning many auxiliary value functions, in addition to optimizing the environmental reward, appears to improve both exploration and representation learning. The question we tackle in this...
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Fall 2013
Many important problems can be cast as state-space problems. In this dissertation we study a general paradigm for solving state-space problems which we name Cluster-and-Conquer (C&C). Algorithms that follow the C&C paradigm use the concept of equivalent states to reduce the number of states...
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Spring 2016
Games have been used as a testbed for artificial intelligence research since the earliest conceptions of computing itself. The twin goals of defeating human professional players at games, and of solving games outright by creating an optimal computer agent, have helped to drive practical ...
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Fall 2022
OpenSpiel is an open-source software system for implementing high-performance software players for many different computer games. Hex is a two-player game of perfect information used in a variety of computer games research projects. The OpenSpiel project has implemented a version of the AlphaZero...