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Browsing by Subject "Reinforcement learning"

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Action priors for learning domain invariances

Author: Rosman, Benjamin S ; Ramamoorthy, S Date: Apr 2015 An agent tasked with solving a number of different decision making problems in similar environments has an opportunity to learn over a longer timescale than each individual task. Through examining solutions to different tasks, it can uncover ... Read more
Applying reinforcement learning to the weapon assignment problem in air defence

Author: Mouton, H ; Roodt, J ; Le Roux, H Date: Dec 2011 The modern battlefield is a fast-paced, information-rich environment, where discovery of intent, situation awareness and the rapid evolution of concepts of operation and doctrine are critical success factors. A combination of the techniques ... Read more
Belief reward shaping in reinforcement learning

Author: Marom, O ; Rosman, Benjamin S Date: Feb 2018 A key challenge in many reinforcement learning problems is delayed rewards, which can significantly slow down learning. Although reward shaping has previously been introduced to accelerate learning by bootstrapping an agent with additional ... Read more
An effective spectrum handoff based on reinforcement learning for target channel selection in the industrial Internet of Things

Author: Oyewobi, SS ; Hancke, GP ; Abu-Mahfouz, Adnan MI ; Onumanyi, Adeiza J Date: Mar 2019 The overcrowding of the wireless space has triggered a strict competition for scare network resources. Therefore, there is a need for a dynamic spectrum access (DSA) technique that will ensure fair allocation of the available network resources ... Read more
Hierarchical subtask discovery with non-negative matrix factorization

Author: Earle, AC ; Saxe, AM ; Rosman, Benjamin S Date: Aug 2017 Hierarchical reinforcement learning methods offer a powerful means of planning flexible behavior in complicated domains. However, learning an appropriate hierarchical decomposition of a domain into subtasks remains a substantial challenge. ... Read more
Hierarchical subtask discovery with non-negative matrix factorization

Author: Earle, AC ; Saxe, AM ; Rosman, Benjamin S Date: Apr 2018 Hierarchical reinforcement learning methods offer a powerful means of planning flexible behavior in complicated domains. However, learning an appropriate hierarchical decomposition of a domain into subtasks remains a substantial challenge. ... Read more
Hierarchy through composition with multitask LMDPs

Author: Saxe, AM ; Earle, AC ; Rosman, Benjamin S Date: Aug 2017 Hierarchical architectures are critical to the scalability of reinforcement learning methods. Most current hierarchical frameworks execute actions serially, with macro-actions comprising sequences of primitive actions. We propose a novel ... Read more
Improving reinforcement learning with ensembles of different learners

Author: Crafford, Gerhardus J ; Rosman, B Date: Nov 2022 Different reinforcement learning (RL) methods exist to address the problem of combining multiple different learners to generate a superior learner. These existing methods usually assume that each learner uses the same algorithm and/or state ... Read more
Learning domain abstractions for long lived robots

Author: Rosman, Benjamin S Date: Jun 2014 Recent trends in robotics have seen more general purpose robots being deployed in unstructured environments for prolonged periods of time. Such robots are expected to adapt to different environmental conditions, and ultimately take on a broader ... Read more
A novel dynamic planning mechanism for allocating electric vehicle charging stations considering distributed generation and electronic units

Author: Adetunji, KE ; Hofsajer, IW ; Abu-Mahfouz, Adnan MI ; Cheng, L Date: Nov 2022 Achieving a sustainable and efficient power systems network and decarbonized environment involves the optimal allocation of multiple distributed energy resource (DERs) unit types and flexible alternating current transmission systems (FACTS) ... Read more
An optimization planning framework for allocating multiple distributed energy resources and electric vehicle charging stations in distribution networks

Author: Adetunji, KE ; Hofsajer, IW ; Abu-Mahfouz, Adnan MI ; Cheng, L Date: Sep 2022 In developing a sustainable and efficient power systems network while reducing carbon footprint, renewable energy (RE)-based Distribution Generation (DG) units are highly recommended. Furthermore, Battery Energy Storage Systems (BESS) and ... Read more
Reinforcement learning-based computation resource allocation scheme for 5G fog-radio access network

Author: Khumalo, Nosipho N ; Oyerinde, O ; Mfupe, Luzango P Date: Apr 2020 Fog computing has emerged as one of the key building blocks of fifth generation mobile networks (5G) because of its ability to effectively meet the demands of real-time or latency-sensitive applications. To introduce fog in 5G, particularly ... Read more
A review of machine learning approaches to power system security and stability

Author: Alimi, OA ; Ouahada, K ; Abu-Mahfouz, Adnan MI Date: Jun 2020 Increasing use of renewable energy sources, liberalized energy markets and most importantly, the integrations of various monitoring, measuring and communication infrastructures into modern power system network offer the opportunity to build ... Read more
Towards energy-efficient intelligent edge computing

Author: Afachao, F ; Abu-Mahfouz, Adnan MI Date: Nov 2023 This research focuses on energy-efficient edge computing in the context of intelligent edge computing. With the increasing demand for computation and data processing at edge network nodes, the study explores the use of artificial intelligence ... Read more

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Browsing by Subject "Reinforcement learning"

Browsing by Subject "Reinforcement learning"

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