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Search results for: offline policy learning
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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublicationThe Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...
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Optimizing Control of Wastewater Treatment Plant With Reinforcement Learning: Technical Evaluation of Twin-Delayed Deep Deterministic Policy Gradient Agent
PublicationControl of the wastewater treatment processes presents significant challenges due to the fluctuating nature of inflow and wastewater composition, alongside the system’s non-linear dynamics. Traditional control methods struggle to adapt to these variations, leading to an economically suboptimal operation of the process and a violation of norms imposed on the quality of wastewater discharged to the catchment area. This study proposes...
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Minerva - A Review of Science, Learning and Policy
Journals -
The Challenge of Quantification: An Interdisciplinary Reading
PublicationThe present work looks at what we call “the multiverse of quantification”, where visible and invisible numbers permeate all aspects and venues of life. We review the contributions of different authors who focus on the roles of quantification in society, with the aim of capturing different and sometimes separate voices. Several scholars, including economists, jurists, philosophers, sociologists, communication and data scientists,...
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Nadzeya Sabatini dr
PeopleNadzeya Sabatini is Assistant Professor in Digital Transformation at Gdańsk University of Technology (Gdansk, Poland), its Department of Informatics in Management (Faculty of Management and Economics). Nadzeya is lecturer at USI – Università della Svizzera italiana (Lugano, Switzerland), a research fellow at the Institute of Digital Technologies for Communication of the same university, and coordinator of MSc in Digital Fashion...
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Environmental Policy
e-Learning CoursesThis course deals with key issues associted with understanding and shaping the environmental policy. Both the general description of the topic and detailed considerations regarding how to shape and execute the environmental policies at the municpal level will be discussed
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Aleksandra Parteka dr hab. inż.
PeopleAbout me: I am an associate professor and head of doctoral studies at the Faculty of Management and Economics, Gdansk University of Technology (GdanskTech, Poland). I got my MSc degree in Economics from Gdansk University of Technology (2003) and Universita’ Politecnica delle Marche (2005), as well as MA degree in Contemporary European Studies from Sussex University (2006, with distinction). I received my PhD in Economics...
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Energy Efficiency and Economic Policy: Comprehensive Theoretical, Empirical, and Policy Review
PublicationIn this paper, we analyze the role of economic policy in prompting energy efficiency. This study reviews three aspects, theoretical, empirical, and existing policies to evaluate the relationship of energy efficiency and economic policy. This study furthermore identifies the existing issues from a policy perspective in energy efficiency. Although not all public policies may be justified, it suggests that these types of financial...
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Energy policy and the role of bioenergy in Poland
PublicationPrzedstawiono sytuacje energetyczną kraju. Omówiono poszczególne sektory wytwarzania energii oraz zapotrzebowania na energię i paliwa. Omówiono przekształcenia sektorów energetycznych w Polsce na przestrzeni lat 1990-2002. Na tym tle przedstawiono techniczne, ekonomiczne, społeczne i prawne aspekty rozwoju energetyki źródeł odnawialnych a w szczególności opartych o bioenergię. Przedstawiono wnioski dla Polski płynące z dotychczasowych...
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Model-free and Model-based Reinforcement Learning, the Intersection of Learning and Planning
PublicationMy doctoral dissertation is intended as the compound of four publications considering: structure and randomness in planning and reinforcement learning, continuous control with ensemble deep deterministic policy gradients, toddler-inspired active representation learning, and large-scale deep reinforcement learning costs.