reward and reinforcement
CONTINUOUS CREATION OF ENTREPRENEURIAL ORIENTATION: A REWARD AND REINFORCEMENT PERSPECTIVE
... between reward and reinforcement system and also risk-taking behaviour fall in line with assertion by Platin and Ergun (2017) who argues that an existence of appropriate reward system encourages a ...
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Homeostatic reinforcement learning for integrating reward collection and physiological stability
... underlying reward is the use- fulness of the corresponding outcome in fulfilling the homeostatic needs of the organism (Cabanac, ...primary reward (equivalently: reinforcer, economic utility) as the approx- ...
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Reward Balancing for Statistical Spoken Dialogue Systems using Multi objective Reinforcement Learning
... using reinforcement learning (RL) where the task is to find an optimal policy π(b) = a which maps the current belief state b—an esti- mate of the user goal— to the next system action ...the reward r, using ...
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Using Semantic Similarity as Reward for Reinforcement Learning in Sentence Generation
... through reinforcement learning (RL). Our ex- periments show that reinforcement learning with semantic similarity reward improves the BLEU scores from the baseline LSTM NMT ...
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Curriculum Learning Based on Reward Sparseness for Deep Reinforcement Learning of Task Completion Dialogue Management
... The problem on sparse and delayed reward ap- pears in reinforcement learning for task oriented dialogue agents. Contrary to single turn interac- tions such as chit-chat or question answering (Ser- ban et ...
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Learning When Not to Answer: a Ternary Reward Structure for Reinforcement Learning Based Question Answering
... In this paper, we addressed the limitations of current approaches for question answering over a knowledge graph that use reinforcement learn- ing. Rather than only returning a correct or in- correct answer, we ...
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Hierarchical Average Reward Reinforcement Learning
... hierarchical reinforcement learning (HRL) to the average reward framework, and investigate two formulations of HRL based on the average reward SMDP ...average reward RL (HAR) algorithms, the ...
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Load Balancing in Heterogeneous Network Using Machine Learning Technique
... If there are some changes in the network environment, the traditional association algorithms must rerun this would cause high cost and also this may lead to poor association in case of highly dynamic environment.The ...
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Sadler_unc_0153D_19140.pdf
... A summary of participant performance on the PST task training is presented in Table A.1. Out of the 104 training trials in the modified Probabilistic Selection Task, participants responded to receive reinforcement ...
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Praise and Reward
... and reward (Kohn, 1998, ...for reinforcement are behaviors desired for a ...the reward they ...and reward must be given with special care to ensure it does not have a negative ...
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Is Reward A Punishment? from Reward Addiction to Sensitivity to Punishment
... on reward practices have started to be revealed through a detailed examination of brain mechanism with technological ...to reward stimuli are largely similar to its reactions to situation of addictive ...
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What is Acceptably Safe for Reinforcement Learning?
... on Reinforcement Learning (RL), where the selection of ‘reward’ and ‘cost’ mechanisms would have a critical effect on the safety outcome of the decisions ...
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The comparison of the efficacy of four behavioural procedures' ability to reduce disruptive behaviour : a thesis presented in partial fulfilment of the requirements for the degree of Master of Arts in Psychology at Massey University
... The procedure the school currently used to reward and discipline the children was compared with response cost plus positive reinforcement, the chance to earn back lost time after a speci[r] ...
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Macquarie University at BioASQ 6b: Deep learning and deep reinforcement learning for query based summarisation
... samples an action from the current global policy plus some perturbation p (line 7) and applies the action (line 11). When all the candidate sentences related to the question have been processed and ac- tioned on (line ...
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Complexity Weighted Loss and Diverse Reranking for Sentence Simplification
... There are two main Seq2Seq models we will compare to in this work, along with the statistical model from Narayan and Gardent (2014). Zhang and Lapata (2017) proposed DRESS (Deep RE- inforcement Sentence Simplification), ...
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Study of Human Hand-Eye Coordination Using Machine Learning Techniques in a Virtual Reality Setup
... inverse reinforcement learning framework was used to visualize different strategies through an interpretation of recov- ered reward values associated with different ...its reward modules according to ...
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Approximate Dynamic Oracle for Dependency Parsing with Reinforcement Learning
... Greedy transition-based dependency parsers trained with static oracles are very efficient but suffer from the error propagation problem. Gold- berg and Nivre (2012, 2013) laid the foundation of dynamic oracles to train ...
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Reinforced Video Captioning with Entailment Rewards
... entailment-corrected reward that checks for logically-directed partial ...Current reinforcement-based text gener- ation works use traditional phrase-matching met- rics ...their reward func- ...based ...
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Early Rumour Detection
... ERD treats incoming posts as a data stream and monitors the posts in real time. When ERD re- ceives a new post, this post — along with all prior posts of the same event — will be used to decide if it constitutes an ...
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Aggression Theories Revisited: Lorenz?s Neoinstinctivism, Wilson?s Socio-Biology and Skinner?s Behavioral Theories
... and reward/punishment) in order to create a desired ...of reward, rather than the punishment and declares that through the proper use of positive reinforcement, the behavior of animals (based on ...
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