Results 41 to 50 of about 98,895 (273)
A Deep Hierarchical Approach to Lifelong Learning in Minecraft
, 2016 We propose a lifelong learning system that has the ability to reuse and transfer knowledge from one task to another while efficiently retaining the previously learned knowledge-base.
Givony, Shahar +4 more
core +1 more source
Applying Hierarchal Clusters on Deep Reinforcement Learning Controlled Traffic Network [PDF]
Menoufia Journal of Electronic Engineering Research, 2020 Traffic congestions is a crucial problem affectingcities around the globe and they are only getting worse as thenumber of vehicles tends to increase significantly. Traffic signalcontrollers are considered as the most important mechanism tocontrol traffic, specifically at intersections, the field of MachineLearning introduces advanced techniques which ...
Ahmed El-Mahalawy +3 more
openaire +2 more sources
Hierarchically Structured Reinforcement Learning for Topically Coherent Visual Story Generation
, 2019 We propose a hierarchically structured reinforcement learning approach to address the challenges of planning for generating coherent multi-sentence stories for the visual storytelling task.
Celikyilmaz, Asli +5 more
core +1 more source
Hierarchical object detection with deep reinforcement learning [PDF]
, 2016 We present a method for performing hierarchical object detection in images guided by a deep reinforcement learning agent. The key idea is to focus on those parts of the image that contain richer information and zoom on them. We train an intelligent agent
Bellver Bueno, Míriam +3 more
core
Enzymatic degradation of biopolymers in amorphous and molten states: mechanisms and applications
FEBS Open Bio, EarlyView.This review explains how polymer morphology and thermal state shape enzymatic degradation pathways, comparing amorphous and molten biopolymer structures. By integrating structure–reactivity principles with insights from thermodynamics and enzyme engineering, it highlights mechanisms that enable efficient polymer breakdown.
Anđela Pustak, Aleksandra Maršavelski
wiley +1 more source
Real-Time Object Navigation With Deep Neural Networks and Hierarchical Reinforcement Learning
IEEE Access, 2020 In the last years, deep learning and reinforcement learning methods have significantly improved mobile robots in such fields as perception, navigation, and planning.
Aleksey Staroverov +5 more
doaj +1 more source
Advanced Functional Materials, EarlyView.Biofabrication aims at providing innovative technologies and tools for the fabrication of tissue‐like constructs for tissue engineering and regenerative medicine applications. By integrating multiple biofabrication technologies, such as 3D (bio) printing with fiber fabrication methods, it would be more realistic to reconstruct native tissue's ...
Waseem Kitana +2 more
wiley +1 more source
Automata guided hierarchical reinforcement learning for zero-shot skill composition [PDF]
, 2017 An obstacle that prevents the wide adoption of (deep) reinforcement learning (RL) in control systems is its need for a large amount of interactions with the environment in order to master a skill.
Belta, Calin, Li, Xiao, Ma, Yao
core
SDRL: Interpretable and Data-efficient Deep Reinforcement Learning Leveraging Symbolic Planning
, 2019 Deep reinforcement learning (DRL) has gained great success by learning directly from high-dimensional sensory inputs, yet is notorious for the lack of interpretability.
Gustafson, Steven +3 more
core +1 more source
Advanced Functional Materials, EarlyView.Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz +3 more
wiley +1 more source