Results 31 to 40 of about 2,392,451 (238)
Using Parameterized Black-Box Priors to Scale Up Model-Based Policy Search for Robotics [PDF]
, 2018 The most data-efficient algorithms for reinforcement learning in robotics are model-based policy search algorithms, which alternate between learning a dynamical model of the robot and optimizing a policy to maximize the expected return given the model ...
Chatzilygeroudis, Konstantinos +1 more
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A Hybrid Revisit Policy For Web Search
Journal of Advances in Information Technology, 2012 A crawler is a program that retrieves and stores pages from the Web, commonly for a Web search engine. A crawler often has to download hundreds of millions of pages in a short period of time and has to constantly monitor and refresh the downloaded pages.
Vipul Sharma, Mukesh Kumar, Renu Vig
doaj +1 more source
Measuring and Visualizing Research Collaboration and Productivity
Journal of Data and Information Science, 2018 This paper presents findings of a quasi-experimental assessment to gauge the research productivity and degree of interdisciplinarity of research center outputs. Of special interest, we share an enriched visualization of research co-authoring patterns.
Garner Jon +3 more
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Tech mining: a revisit and navigation
Frontiers in Research Metrics and AnalyticsThis mini-review arrays the pertinent tools and purposes of “Tech Mining” – shorthand for empirical analyses of Science, Technology and Innovation (ST&I) data. The intent is to introduce the range of tools, and show how they can complement each other.
Alan L. Porter +3 more
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Bio-based and Applied Economics, 2019 Both the revised EU Bioeconomy strategy and the proposals for the Common Agricultural Policy (CAP) 2021-2027 were released in 2018. This paper explores the connection between these two policy areas, the needs for economic and policy research and the way ...
Davide Viaggi
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Evolutionary Reinforcement Learning: A Systematic Review and Future Directions
MathematicsIn response to the limitations of reinforcement learning and Evolutionary Algorithms (EAs) in complex problem-solving, Evolutionary Reinforcement Learning (EvoRL) has emerged as a synergistic solution.
Yuanguo Lin +6 more
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Policy Search Reinforcement Learning Method in Latent Space [PDF]
Jisuanji kexue yu tansuoPolicy search is an efficient learning method in the field of deep reinforcement learning (DRL), which is capable of solving large-scale problems with continuous state and action spaces and widely used in real-world problems. However, such method usually
ZHAO Tingting, WANG Ying, SUN Wei, CHEN Yarui, WANG Yuan, YANG Jucheng
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OPTIMAL STABILIZATION POLICY WITH SEARCH EXTERNALITIES [PDF]
Macroeconomic Dynamics, 2013 We study optimal monetary stabilization policy in a DSGE model with microfounded money demand. A search externality creates “congestion,” which causes aggregate output to be inefficient. Because of the informational frictions that give rise to money, households are unable to insure themselves perfectly against aggregate shocks.
Berentsen, Aleksander +1 more
openaire +2 more sources
Curiosity Creates Diversity in Policy Search
ACM Transactions on Evolutionary Learning and Optimization, 2023 When searching for policies, reward-sparse environments often lack sufficient information about which behaviors to improve upon or avoid. In such environments, the policy search process is bound to blindly search for reward-yielding transitions and no early reward can bias this search in one direction or another.
Paul-Antoine Le Tolguenec +3 more
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Adaptive Control with Approximated Policy Search Approach
ITB Journal of Engineering Science, 2010 Most of existing adaptive control schemes are designed to minimize error between plant state and goal state despite the fact that executing actions that are predicted to result in smaller errors only can mislead to non-goal states. We develop an adaptive
Agus Naba
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