hierarchical reinforcement
Human Like Decision Making: Document level Aspect Sentiment Classification via Hierarchical Reinforcement Learning
... In summary, we formulate the task of DASC as a semi-Markov Decision process (Sutton et al., 1999b), i.e., hierarchical reinforcement learning with a high-level policy and a low-level policy. In particular, ...
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Sub domain Modelling for Dialogue Management with Hierarchical Reinforcement Learning
... flat reinforcement learning methods do not provide an efficient frame- work for modelling such ...for hierarchical reinforcement learning us- ing the option ...
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Hierarchical Reinforcement Learning and Hidden Markov Models for Task Oriented Natural Language Generation
... Surface realisation decisions in a Natural Language Generation (NLG) system are often made accord- ing to a language model of the domain (Langkilde and Knight, 1998; Bangalore and Rambow, 2000; Oh and Rudnicky, 2000; ...
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Interactive Semantic Parsing for If-Then Recipes via Hierarchical Reinforcement Learning
... Given a text description, most existing semantic parsers syn- thesize a program in one shot. However, it is quite challenging to produce a correct program solely based on the description, which in reality is often ...
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Hierarchical Reinforcement Learning for Course Recommendation in MOOCs
... Although the basic recommendation models can estimate an attention coefficient for each historical course, the ef- fects of the contributing courses to the target one may be diluted by the irrelevant ones when users ...
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Diversity-Driven Extensible Hierarchical Reinforcement Learning
... Hierarchical reinforcement learning (HRL) has recently shown promising advances on speeding up learning, improv- ing the exploration, and discovering intertask transferable ...
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Combining Hierarchical Reinforcement Learning and Bayesian Networks for Natural Language Generation in Situated Dialogue
... use Hierarchical Reinforcement Learning (HRL) with Bayesian networks to achieve ...this. Reinforcement learning (RL) is an attractive framework for opti- mising NLG systems, where situations are ...
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Hierarchical Reinforcement Learning for Adaptive Text Generation
... chical reinforcement learning to text genera- tion in the wayfinding ...chical reinforcement learning to learn a gen- eration policy that captures these interdepen- dencies, and that can be transferred to ...
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A Hierarchical Framework for Relation Extraction with Reinforcement Learning
... Most existing methods determine relation types only after all the entities have been recognized, thus the interaction be- tween relation types and entity mentions is not fully mod- eled. This paper presents a novel ...
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Autonomous Sub domain Modeling for Dialogue Policy with Hierarchical Deep Reinforcement Learning
... task. Hierarchical reinforcement learning (HRL) (Dietterich, 2000; Parr and Rus- sell, 1997) is a technique to model complex di- alogues (Cuay´ahuitl, ...
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Hierarchical Average Reward Reinforcement Learning
... on hierarchical reinforcement learning (HRL) to the average reward framework, and investigate two formulations of HRL based on the average reward SMDP ...a hierarchical policy within the space of ...
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Bending Stiffness of Truss Reinforced Steel Concrete Composite Beams
... shear reinforcement on the final bending stiffness of the ...shear reinforcement can lead to significant increments in the bending stiffness of the ...shear reinforcement influence on J eq ( ζ ω , ) ...
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Microstructure Control of Particle Reinforced Metal Matrix Composites Fabricated by Low Pressure Infiltration Process*
... into fine (particle size: 50 µm under) and coarse (particle size: 50–100 µm) powders. The mixed powder consisting of re- inforcement particles and pure aluminum particles (particle size: 100 µm) in various volume ...
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The Bond Strength of Glass Fiber Reinforced Polymer (GFRP) Reinforcement with Monolith Concrete
... conventional reinforcement is its ability against corrosion makes it suitable for structures directly related to land, water, and corrosive ...a reinforcement to hold the shear ...GFRP reinforcement ...
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SANCTION ENFORCEMEMT MECHANISMS IN ARTIFICIAL AGENT SOCIETIES- A GLANCE
... Sanction Reinforcement: After new norms come into existence, new sanctions are also created and enforced.. This phase is termed as sanction reinforcement..[r] ...
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Current advancement and Research Development in Copper Composites fabricated by Powder Metallurgy: A Review
... In general term Frictional Coefficient (FC) could be defined as the minimum force needed to allow the surfaces to start sliding, divided by the force pressing acting on the contact surfaces. In material science FC plays ...
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Aluminium Based Metal Matrix Composites: A Review of Reinforcement; Mechanical, Wear Properties
... Anilkumar et.al. [12] produced three sets of Al (Al6061) metal matrix composites reinforced with fly ash of particle sizes 75-100, 45-50 and 4-25 μm with the weight fractions of 10, 15 and 20%.The author observed that ...
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Closed-form analytical solution procedure for element design in D regions
... of reinforcement in D regions (Amini Najafian and Vollum, ...of reinforcement required to satisfy the design constraints subject to practical detailing ...optimised reinforcement designs sacrificing ...
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Application of Geosynthetics in Pavement Design
... A geotextile reduces subgrade deformation when it uses at the top of the subgrade and it performs better than a geogrid as a separator between subgrade and base [19] as shown in Fig. 7. Under dynamic traffic loading, ...
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Behaviorism in Education.doc
... Behaviorist techniques have long been employed in education to promote behavior that is desirable and discourage that which is not. Among the methods derived from behaviorist theory for practical classroom application ...
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