Using Generative Adversarial Networks to Develop a Realistic Human Behavior Simulator

Abstract

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Generative Adversarial Networks and Its Applications in Biomedical Informatics

“…Their study showed that fine tuning with GAN can improve performance. Hassouni et al (93) used GAN with LSTM to generate realistic simulation environments based on the WISDM dataset. Their results showed that the model trained on the data artificially generated by the GAN had similar performance trained on real data.…”

End-to-end Personalization of Digital Health Interventions using Raw Sensor Data with Deep Reinforcement Learning

“…In this work we rely on RL to achieve end-to-end personalization of health interventions based on sensed data from devices. We test our algorithm in a simulation environment that relies on a behavior engine and Generative Adversarial Networks (GANs) [2] for generating low-level sensor data (accelerometer data). To answer our main research question we formulated the following sub-questions that outline our experiments:…”

“…Our second contribution is a comparison of the intervention performance between different levels of state representations using our framework. To make these comparisons we exploit a simulation environment put forward in [2]. State representations range from unprocessed, raw sensor data, to raw data augmented with high-level features.…”

Spectrum of Advancements and Developments in Multidisciplinary Domains for Generative Adversarial Networks (GANs)

“…Bass, drums, guitar, piano and strings Proposed three models known as call jamming model, composer model and hybrid model for music generation Yu et al [41] 2019 Simultaneous generation of lyrics-conditioned melody and association alignment between syllables of given lyrics by using conditional deep Lstm generator and discriminator Deep generative model for generation of melody and notes of predicted melody Weather forecasting Chen et al [42] 2018 Scenario generation used for weather forecasting, however errors become more pronounced when the typhoons move into deep sea Advantage: generates wind patterns and weather forecasts based on historic data Ruttgers et al [43] 2018 Predict track of typhoons by using satellite image. If information about surface pressure, velocity and sea surface temperature are added the results can become more accurate Advantage: predict the typhoon center as well as the movement of clouds with certain margins for error Sports Jiao et al [44] 2018 Distinguishes correct performed golf swings Achieved accuracy and precision both in identification as well as classification of golf swings Deverall et al [45] 2017 Conditional GAN for designing athletic shoes based on google gnet Achieved shoes categorization according to their physical attributes as well as functional type Internet of things (IoT) Wang et al [46] 2018 Use of Bayesian methods for Radio Frequency (RF) sensing for IoT Advantage: overcome limitation of limited data availability by introducing an offline stage Zhao et al [47] 2018 Individual identity authentication by applying open-categorical classification model based on gan (occ-gan) Advantage: better results are achieved than other methods like one-class support vector machine (oc-svm) and one-versus-rest support vector machine (ovr-svm) Genetic engineering Dizaji et al [48] 2018 Gene expression profiling by using semi-supervised GAN for expression inference Use landmark genes instead of whole gene expressions Simulation and modeling Hassouni et al [49] 2018 Generating realistic simulation environments that simulates daily activities of users Advantage: generate realistic sensory data that related to daily activities of users Pöpperl et al [50] 2019 Synthetic ultrasonic signal simulation using conditional gans (cgans) Advantage: real like data augmentation for automotive ultrasonic and also adaptive to external influences Market prediction and forecasting Tian et al [51] 2019 A technique for predicting the consumption of energy Advantage: outperforms the standard approaches i.e. information diffusion technology (idt), the heuristic mega-trend-diffusion (hmtd) technology and the bootstrap technique Advantage: scalable to perform forecast for demand of electricity and the traffic supply Luo et al [52] 2018 A technique for predicting the prices of the crude oil using adap- [55] 2019 Double P-buried layers MISFET (DP-MISFET) is proposed Simulated and characteristics are analysed by the Sentaurus TCAD tool Road network generation and path planning Albert et al [56] 2018 Novel techniq...…”

“…In [49] the authors propose to use GANs for generating realistic simulation environments and applied a prevailing simulator to simulate routine tasks of users and to create realistic sensory logs that supplements such routine tasks. The simulator can easily be trained and tested by the GAN based approach and assessment demonstrated same level of performance on synthetic data as delivered real dataset.…”