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Interactive Control of Diverse Complex Characters with Neural Networks

Igor Mordatch, Kendall Lowrey, Galen Andrew, Zoran Popovic, Emanuel Todorov
2015 Neural Information Processing Systems  
We present a method for training recurrent neural networks to act as near-optimal feedback controllers.  ...  The controller is a neural network, having a large number of feed-forward units that learn elaborate state-action mappings, and a small number of recurrent units that implement memory states beyond the  ...  Conclusions and Future Work We have presented an automatic way of generating neural network parameters that represent a control policy for physically consistent interactive character control, only requiring  ... 
dblp:conf/nips/MordatchLAPT15 fatcat:au2jx6jg35fjtkd4x5gc6vv4sa

Neural MoCon: Neural Motion Control for Physically Plausible Human Motion Capture [article]

Buzhen Huang, Liang Pan, Yuan Yang, Jingyi Ju, Yangang Wang
2022 arXiv   pre-print
Qualitative and quantitative results show that we can obtain physically plausible human motion with complex terrain interactions, human shape variations, and diverse behaviors.  ...  Finally, we regress the sampling distribution from the current state of the physical character with the trained prior and sample satisfied target poses to track the estimated reference motion.  ...  In addition, with the sampling, the neural motion control is more general to complex terrain, body shape variations, and diverse behaviors.  ... 
arXiv:2203.14065v1 fatcat:jwc7bxqrirguliv3jmbuznqari

Optimizing Character Animations using Online Crowdsourcing [article]

Benjamin Kenwright
2022 arXiv   pre-print
This paper presents a novel approach for exploring diverse and expressive motions that are physically correct and interactive.  ...  Our system combines the expressive power of web pages for visualising content on-the-fly with a fully fledged interactive (physics-based) animation solution that includes a rich set of libraries.  ...  The also includes dealing with multiple characters in the context of character-character interaction and manipulation [11] .  ... 
arXiv:2206.15149v1 fatcat:eifrewofdbg2jlsf7rmtbvo6rm

Evolving Plastic Neuromodulated Networks for Behavior Emergence of Autonomous Virtual Characters

Yuri Nogueira, Carlos F. de Brito, Creto Vidal, Joaquim Cavalcante-Neto
2013 Advances in Artificial Life, ECAL 2013  
a simple novel method for genetic encoding of artificial neural networks.  ...  In this work, we present the tools that we have been using to study that idea: a controller based on a plastic neuromodulated neural network, which is capable of molding itself to received stimuli; and  ...  To do that, the alignment score is based on a network-specific interaction map that leads to a complex chromosomal representation.  ... 
doi:10.7551/978-0-262-31709-2-ch083 dblp:conf/ecal/NogueiraBVN13 fatcat:vxvjfsrm7fazrcghjtiu4f572u

Conversation Modeling with Neural Network

Jivan Y. Patil, Girish P. Potdar
2018 Asian Journal of Research in Computer Science  
This paper proposes a simple approach based on use of neural networks' recently proposed sequence to sequence framework.  ...  Although DNNs work well with availability of large labeled training set, it cannot be used to map complex structures like sentences end-to-end.  ...  Allowing researchers to explore application of neural networks for more complex tasks like text generation.  ... 
doi:10.9734/ajrcos/2018/v1i324738 fatcat:f226jjtlebe7vl6rafbuzwkviy

Evolving neural networks

Risto Miikkulainen
2007 Proceedings of the 2007 GECCO conference companion on Genetic and evolutionary computation - GECCO '07  
to actions • Large/continuous states and actions easy -Generalization in neural networks • Hidden states disambiguated through memory -Recurrency in neural networks 69 6 • Evolution encourages diversity  ...  . • Solution: Start with minimal structure and complexify -Hidden nodes, connections, input features 79 Minimal Starting Networks Population of Diverse Topologies Generations pass...  ... 
doi:10.1145/1274000.1274119 dblp:conf/gecco/Miikkulainen07 fatcat:4zyvbu3dxjb4hjqqicvwwzvjna

A Survey on Deep Learning for Skeleton-Based Human Animation [article]

L. Mourot, L. Hoyet, F. Le Clerc, François Schnitzler
2021 arXiv   pre-print
To this end, deep neural networks drive most recent advances through deep learning and deep reinforcement learning.  ...  Second, we cover state-of-the-art approaches divided into three large families of applications in human animation pipelines: motion synthesis, character control and motion editing.  ...  Interactions DRL has also been used to animate characters interacting with other characters and complex objects.  ... 
arXiv:2110.06901v1 fatcat:abppln4rbbeufiw4z6a3wnk7oy

Recognition and Generation of Sentences through Self-organizing Linguistic Hierarchy Using MTRNN [chapter]

Wataru Hinoshita, Hiroaki Arie, Jun Tani, Tetsuya Ogata, Hiroshi G. Okuno
2010 Lecture Notes in Computer Science  
These studies have found that some kinds of recurrent neural networks could learn grammar.  ...  We show that a Multiple Timescale Recurrent Neural Network (MTRNN) can acquire the capabilities of recognizing and generating sentences by self-organizing a hierarchical linguistic structure.  ...  This capability is essential for dealing with the diversity of expressions in language. Thus, it is also important to find whether a neural system can acquire such hierarchical structures.  ... 
doi:10.1007/978-3-642-13033-5_5 fatcat:enhbtfdllfdohg2kzvmqhjfhby

Complex Deep Learning and Evolutionary Computing Models in Computer Vision

Li Zhang, Chee Peng Lim, Jungong Han
2019 Complexity  
features extracted from depth images by using a multimodal deep feature fusion model. e proposed model consists of four deep convolutional neural networks (CNNs).  ...  . e advent of deep learning and associated paradigms such as evolutionary computing models has propelled computer vision to the next level, solving a variety of complex problems in diverse applications  ...  A simple frame structure of so ware defined network and network function virtualization technologies, coupled with the autoencoder in the sink and control nodes of the wireless sensor network, is constructed  ... 
doi:10.1155/2019/1671340 fatcat:wars4wlyxbc5rgf2huppco2gmu

Neuroevolution: from architectures to learning

Dario Floreano, Peter Dürr, Claudio Mattiussi
2008 Evolutionary Intelligence  
Artificial neural networks (ANNs) are applied to many real-world problems, ranging from pattern classification to robot control.  ...  In order to design a neural network for a particular task, the choice of an architecture (including the choice of a neuron model), and the choice of a learning algorithm have to be addressed.  ...  Their results indicate that for tasks with memory dependent dynamics, spiking neural networks can provide less complex solutions.  ... 
doi:10.1007/s12065-007-0002-4 fatcat:h7vs7pui5bb23he7gdawtio7m4

Stochastic Scene-Aware Motion Prediction [article]

Mohamed Hassan, Duygu Ceylan, Ruben Villegas, Jun Saito, Jimei Yang, Yi Zhou, Michael Black
2021 arXiv   pre-print
It is necessary to model this diversity when synthesizing virtual humans that realistically perform human-scene interactions.  ...  Our method, called SAMP, for Scene-Aware Motion Prediction, generalizes to target objects of various geometries while enabling the character to navigate in cluttered scenes.  ...  For helping with the data collection, we are grateful to Tsvetelina Alexiadis, Galina Henz, Markus Höschle and Tobias Bauch.  ... 
arXiv:2108.08284v1 fatcat:f4gtnwgs3rh6nh57s5qnvo2cdy

Structure of regulatory networks and dynamics of bio-molecules: Predicting unknown from known

Atsushi Mochizuki, Daisuke Saito
2010 Developmental Biology  
stability, interactions with specific KRAB domain proteins, or recruitment of chromatin modifying enzymes.  ...  of TRIM28, provided genetic evidence for the functional significance of a ZFP568/TRIM28 interaction. chatwo mutants, isolated in a forward mutagenesis screen, arrest at embryonic day 9 (E9) with defect  ...  Regulatory relations between biological molecules constitute complex network systems, and realize diverse biological functions through the dynamics of molecular activities.  ... 
doi:10.1016/j.ydbio.2010.05.448 fatcat:5566oisw25g63onwlf22fkw5mm

STRUCTURAL SYNTHESIS OF HYBRID NEURAL NETWORKS ENSEMBLES

V. M. Sineglazov, O. I. Chumachenko, O. R. Bedukha
2018 Electronics and Control Systems  
It is considered the structural synthesis of hybrid neural networks ensembles. It is chosen the ensemble topology as parallel structure with united layer.  ...  It is developed a hybrid algorithm for the problem solution which includes some algorithms preliminary choice of classifiers(modules of neural networks-hybrid neural networks, which consist of Kohonen,  ...  It becomes possible to create a large number of areas, which will lead to excessive clustering of space and will create a large group of basic ANNs with a complex mechanism of interaction through the networks  ... 
doi:10.18372/1990-5548.57.13242 fatcat:jtm7ead2kjbyxlytqr4ho2nlym

THE DEVELOPMENT OF A MODEL OF A NUMBER PLATE RECOGNITION SYSTEM CONTROL IN REAL TIME

Aizhan Soltangalievna Tlebaldinova, Natalya Fedorovna Denissova
2014 Theoretical & Applied Science  
The paper represents the model of a number plate recognition system control in real time which allows to optimally manage the load of a computer system.  ...  The developed model allows the flexibility to manage the process of license plate recognition using not only the parameters of the process of recognition but also a variety of scenarios that define the  ...  After analyzing the known plate recognition systems the following was revealed: firstly, many systems give unsatisfactory results for images of poor quality; secondly, they do not work with complex (diverse  ... 
doi:10.15863/tas.2014.04.12.4 fatcat:3r2rbvptkngznhgzkv3cdxi574

Précis of After Phrenology: Neural Reuse and the Interactive Brain

Michael L. Anderson
2015 Behavioral and Brain Sciences  
A diverse behavioral repertoire is achieved by means of the creation of multiple, nested, and overlapping neural coalitions, in which each neural element is a member of multiple different coalitions and  ...  cooperates with a different set of partners at different times.  ...  ; a voxel from left anterior insula with a high diversity value of 0.88; and a voxel from left thalamus with a diversity value of 0.76, equal to the population median.  ... 
doi:10.1017/s0140525x15000631 pmid:26077688 fatcat:vvia56wl3zaullaw2odf3wvt2i
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