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Spatial reasoning and planning for deep embodied agents
Published 2024“…SOAP showed robust performances on history-conditional corridor tasks as well as classical benchmarks such as Atari.</p> <p>Thirdly, LangProp, a code optimisation framework using Large Language Models to solve embodied agent problems that require reasoning by treating code as learnable policies. …”
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Acute stress imparts a transient benefit to task-switching that is not modulated following a single bout of exercise
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Evaluation of Biogas Production from the Co-Digestion of Municipal Food Waste and Wastewater Sludge at Refugee Camps Using an Automated Methane Potential Test System
Published 2018-12-01“…The potential benefits of the application of a circular economy—converting biomass at Za'atari Syrian refugee camps into energy—was investigated in this study. …”
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Micro scale level rainfall trend analysis at Madhira, Khammam district of Telangana
Published 2023-03-01Get full text
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Pathogens are linked to human moral systems across time and space
Published 2022-01-01Get full text
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Using Sentinel-2 to Track Field-Level Tillage Practices at Regional Scales in Smallholder Systems
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Improving sample efficiency using attention in deep reinforcement learning
Published 2021“…On the next experiment, we tested SAN, C-SAN and CAN on 49 Atari 2600 games. C-SAN was found to be better than the No Attention model by 15.36% on average while CAN and SAN were found to be worse by -14.44% and -1.47% respectively. …”
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Intrarenal Dopaminergic System Is Dysregulated in SS-<i>Resp18<sup>mutant</sup></i> Rats
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Explaining Deep Q-Learning Experience Replay with SHapley Additive exPlanations
Published 2023-10-01“…We investigate training a Deep Convolutional Q-learning agent across 20 Atari games intentionally reducing Experience Replay capacity from <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn><mo>×</mo><msup><mn>10</mn><mn>6</mn></msup></mrow></semantics></math></inline-formula> to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>5</mn><mo>×</mo><msup><mn>10</mn><mn>2</mn></msup></mrow></semantics></math></inline-formula>. …”
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Measuring stakeholders' perception of Sansad Adarsh Gram Yojana
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