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Deep Reinforcement Learning-based Portfolio Management
(2019-05-16)
Machine Learning is at the forefront of every field today. The subfields of Machine Learning called Reinforcement Learning and Deep Learning, when combined have given rise to advanced algorithms which have been successful ...
Optimal control strategies and reinforcement learning for dynamical multiagent systems in graphical games
(2019-07-02)
As the number of autonomous agents increases in industrial and urban areas, the development of formal protocols to analyze their behavior as they interact with each other becomes of central interest in control systems ...
LONG-DISTANCE AND BROAD-BAND AERIAL COMMUNICATION USING DIRECTIONAL ANTENNAS: THEORY, IMPLEMENTATION, AND APPLICATIONS
(2019-08-05)
Unmanned aerial vehicles (UAV) have found broad civilian applications. However, existing commercial usages are limited to single UAVs. To facilitate commercial multi-UAV applications, robust UAV-to-UAV communication with ...
Learning Representations Using Reinforcement Learning
(2019-05-09)
The framework of reinforcement learning is a powerful suite of algorithms that can learn generalized solutions to complex decision making problems. However, the applications of reinforcement learning algorithms to traditional ...
LEARNING TRANSFERABLE META-POLICIES FOR HIERARCHICAL TASK DECOMPOSITION AND PLANNING COMPOSITION
(2019-12-16)
In real world scenarios where situated agents are faced with dynamic, high-dimensional, partially observable environments with action and reward uncertainty, the traditional states space Reinforcement Learning (RL) becomes ...
LEARNING ROBOT MANIPULATION TASKS VIA OBSERVATION
(2019-12-06)
The coexistence of humans and robots has been the aspiration of many scientific endeavors in the past century. Most anthropomorphic or industrial robots are highly articulated and complex machines, which are designed to ...