Futures of artificial intelligence through technology readiness levels

[1]  Ferenc Szidarovszky,et al.  A multi-objective train scheduling model and solution , 2004 .

[2]  G. Banks.  Artificial intelligence in medical diagnosis: the INTERNIST/CADUCEUS approach. , 1986, Critical reviews in medical informatics.

[3]  Ethem Alpaydin,et al.  Introduction to machine learning , 2004, Adaptive computation and machine learning.

[4]  Monica N. Nicolescu,et al.  Understanding human intentions via Hidden Markov Models in autonomous mobile robots , 2008, 2008 3rd ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[5]  Jure Leskovec,et al.  Complete the Look: Scene-Based Complementary Product Recommendation , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[6]  Peter A. Flach,et al.  Machine Learning - The Art and Science of Algorithms that Make Sense of Data , 2012 .

[7]  Isabelle Bichindaritz,et al.  Report on the Eighteenth International Conference on Case-Based Reasoning , 2012, AI Mag..

[8]  Alexander J. Smola,et al.  Fair and balanced: learning to present news stories , 2012, WSDM '12.

[9]  Gokhan Tur,et al.  Spoken Language Understanding: Systems for Extracting Semantic Information from Speech , 2011 .

[10]  Vaidyanathan Jayaraman,et al.  Expert systems in production and operations management: Current applications and future prospects , 1996 .

[11]  Melissa A. Schilling.  Technological Lockout: An Integrative Model of the Economic and Strategic Factors Driving Technology Success and Failure , 1998 .

[12]  William P. Wagner.  Trends in expert system development: A longitudinal content analysis of over thirty years of expert system case studies , 2017, Expert Syst. Appl..

[13]  Philip Webb,et al.  The development of a Human Factors Readiness Level tool for implementing industrial human-robot collaboration , 2017 .

[14]  Carina Friedrich Dorneles,et al.  Automated Expertise Retrieval , 2019, ACM Comput. Surv..

[15]  Uwe Muegge.  Fully automatic high quality machine translation of restricted text: A case study , 2006 .

[16]  Raymond W. Ptucha,et al.  Intelligent character recognition using fully convolutional neural networks , 2019, Pattern Recognit..

[17]  José Hernández-Orallo,et al.  The Measure of All Minds: Evaluating Natural and Artificial Intelligence , 2017 .

[18]  H. Lieberman.  Your Wish is My Command: Programming By Example , 2001 .

[19]  A.K. Takmazian,et al.  Rail Transport Control by Combinatorial Optimization Approach , 2017, 2017 IEEE 11th International Conference on Application of Information and Communication Technologies (AICT).

[20]  ByoungChul Ko,et al.  A Brief Review of Facial Emotion Recognition Based on Visual Information , 2018, Sensors.

[21]  Michael Wooldridge,et al.  Introduction to multiagent systems , 2001 .

[22]  Peter M. Verderame,et al.  Planning and Scheduling under Uncertainty: A Review Across Multiple Sectors , 2010 .

[23]  Lior Rokach,et al.  Introduction to Recommender Systems Handbook , 2011, Recommender Systems Handbook.

[24]  Haibin Cheng,et al.  Real-time Personalization using Embeddings for Search Ranking at Airbnb , 2018, KDD.

[25]  Arne Hintz,et al.  Digital Citizenship in a Datafied Society , 2018 .

[26]  Chris Fox,et al.  The Handbook of Computational Linguistics and Natural Language Processing , 2010 .

[27]  Pablo Noriega,et al.  Towards a Test-Bed for Trading Agents in Electronic Auction Markets , 1998, AI Commun..

[28]  Bin Shen,et al.  Newspaper coverage of artificial intelligence: A perspective of emerging technologies , 2020, Telematics Informatics.

[29]  N. R. Jennings,et al.  To appear in: Int Journal of Group Decision and Negotiation GDN2000 Keynote Paper Automated Negotiation: Prospects, Methods and Challenges , 2022 .

[30]  Noam Brown,et al.  Superhuman AI for multiplayer poker , 2019, Science.

[31]  R. Sarkar,et al.  Handwritten Word Recognition Using MLP based Classifier: A Holistic Approach , 2013 .

[32]  Sumit Gulwani,et al.  Spreadsheet data manipulation using examples , 2012, CACM.

[33]  Vicent J. Botti,et al.  Agreement technologies and their use in cloud computing environments , 2012, Progress in Artificial Intelligence.

[34]  Pavel V. Sevastjanov,et al.  A stock trading expert system based on the rule-base evidential reasoning using Level 2 Quotes , 2012, Expert Syst. Appl..

[35]  Koen V. Hindriks,et al.  Negotiating Agents , 2012, AI Mag..

[36]  Sarvapali D. Ramchurn,et al.  Putting the 'smarts' into the smart grid , 2012, Commun. ACM.

[37]  Ulrich A. K. Betz,et al.  Surveying the future of science, technology and business – A 35 year perspective , 2019, Technological Forecasting and Social Change.

[38]  Sarit Kraus,et al.  Principles of Automated Negotiation , 2014 .

[39]  Sumit Gulwani,et al.  Inductive programming meets the real world , 2015, Commun. ACM.

[40]  Nikolai Smolyanskiy,et al.  Toward low-flying autonomous MAV trail navigation using deep neural networks for environmental awareness , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[41]  R K Narla Siva,et al.  コネクテッドビークル技術の進化:スマートドライバーからスマートカーへ...自律運転自動車へ | 文献情報 | J-GLOBAL 科学技術総合リンクセンター , 2013 .

[42]  Roland Olsson,et al.  Inductive Functional Programming Using Incremental Program Transformation , 1995, Artif. Intell..

[43]  Richard Szeliski,et al.  Computer Vision - Algorithms and Applications , 2011, Texts in Computer Science.

[44]  Past, Present, and Future of Recommender Systems: An Industry Perspective , 2016, RecSys.

[45]  Dong Yu,et al.  Conversational Speech Transcription Using Context-Dependent Deep Neural Networks , 2012, ICML.

[46]  Lianwen Jin,et al.  DropSample: A New Training Method to Enhance Deep Convolutional Neural Networks for Large-Scale Unconstrained Handwritten Chinese Character Recognition , 2015, Pattern Recognit..

[47]  Trevor Darrell,et al.  A geometric approach to robotic laundry folding , 2012, Int. J. Robotics Res..

[48]  Nigel H. M. Wilson,et al.  Modeling real-time control strategies in public transit operations , 1999 .

[49]  Henrik Andersson,et al.  Containership Routing and Scheduling in Liner Shipping: Overview and Future Research Directions , 2014, Transp. Sci..

[50]  Rose Holley,et al.  How Good Can It Get? Analysing and Improving OCR Accuracy in Large Scale Historic Newspaper Digitisation Programs , 2009, D Lib Mag..

[51]  Georg Buchner,et al.  Specifying Technology Readiness Levels for the Chemical Industry , 2019, Industrial & Engineering Chemistry Research.

[52]  Murray Campbell,et al.  I-athlon: Towards A Multidimensional Turing Test , 2016, AI Mag..

[53]  Johannes M. Bauer,et al.  Techno-unemployment: A framework for assessing the effects of information and communication technologies on work , 2018, Telematics Informatics.

[54]  Einar Søreide Johansen.  Personalized Content Creation using Recommendation Systems , 2018 .

[55]  Tim Miller,et al.  The Minds of Many: Opponent Modeling in a Stochastic Game , 2017, IJCAI.

[56]  Hassan Ugail,et al.  Deep face recognition using imperfect facial data , 2019, Future Gener. Comput. Syst..

[57]  John F. Muratore,et al.  The INCO Expert System Project: CLIPS in Shuttle mission control , 1990 .

[58]  Peter McBurney,et al.  Games That Agents Play: A Formal Framework for Dialogues between Autonomous Agents , 2002, J. Log. Lang. Inf..

[59]  Paul Covington,et al.  Deep Neural Networks for YouTube Recommendations , 2016, RecSys.

[60]  Pieter Jan Stappers,et al.  Co-creation and the new landscapes of design , 2008 .

[61]  Roberto Paredes,et al.  Local Deep Neural Networks for gender recognition , 2016, Pattern Recognit. Lett..

[62]  Verónica Romero,et al.  Image-speech combination for interactive computer assisted transcription of handwritten documents , 2019, Comput. Vis. Image Underst..

[63]  Xiaolong Zhang,et al.  CollabSeer: a search engine for collaboration discovery , 2011, JCDL '11.

[64]  Valeria De Antonellis,et al.  PREFer: A prescription-based food recommender system , 2017, Comput. Stand. Interfaces.

[65]  GonçalvesRodrigo,et al.  Automated Expertise Retrieval , 2019 .

[66]  Feipeng Da,et al.  Efficient 3D face recognition handling facial expression and hair occlusion , 2012, Image Vis. Comput..

[67]  Koen Hindriks Man-Machine.  Avoiding Approximation Errors in Multi-Issue Negotiation with Issue Dependencies , 2008 .

[68]  José Hernández-Orallo,et al.  Does AI Qualify for the Job?: A Bidirectional Model Mapping Labour and AI Intensities , 2020, AIES.

[69]  Xiaolei Ma,et al.  Joint optimization of scheduling and capacity for mixed traffic with autonomous and human-driven buses: A dynamic programming approach , 2020 .

[70]  John Salvatier,et al.  When Will AI Exceed Human Performance? Evidence from AI Experts , 2017, ArXiv.

[71]  Henry Lieberman,et al.  Watch what I do: programming by demonstration , 1993 .

[72]  David Sarne,et al.  Effective deadlock resolution with self-interested partially-rational agents , 2014, Annals of Mathematics and Artificial Intelligence.

[73]  Michael P. Wellman.  Trading Agents , 2011, Trading Agents.

[74]  Catholijn M. Jonker,et al.  When Will Negotiation Agents Be Able to Represent Us? The Challenges and Opportunities for Autonomous Negotiators , 2017, IJCAI.

[75]  Chen Fang,et al.  Visually-Aware Fashion Recommendation and Design with Generative Image Models , 2017, 2017 IEEE International Conference on Data Mining (ICDM).

[76]  Yi Tay,et al.  Deep Learning based Recommender System: A Survey and New Perspectives , 2018 .

[77]  Enrique Vidal,et al.  Probabilistic multi-word spotting in handwritten text images , 2018, Pattern Analysis and Applications.

[78]  Raul Fernandez-Fernandez,et al.  Enabling garment-agnostic laundry tasks for a Robot Household Companion , 2020, Robotics Auton. Syst..

[79]  Dario Pacciarelli,et al.  Reordering and Local Rerouting Strategies to Manage Train Traffic in Real Time , 2008, Transp. Sci..

[80]  Michael Kaisers,et al.  The Value of Information in Automated Negotiation: A Decision Model for Eliciting User Preferences , 2017, AAMAS.

[81]  Demis Hassabis,et al.  Mastering the game of Go with deep neural networks and tree search , 2016, Nature.

[82]  Cynthia Breazeal,et al.  Machine behaviour , 2019, Nature.

[83]  R. Kurzweil,et al.  The Singularity Is Near: When Humans Transcend Biology , 2006 .

[84]  Ulrich Paquet,et al.  Beyond Collaborative Filtering: The List Recommendation Problem , 2016, WWW.

[85]  Matthew B Hoy.  Alexa, Siri, Cortana, and More: An Introduction to Voice Assistants , 2018, Medical reference services quarterly.

[86]  Mehrbakhsh Nilashi,et al.  A knowledge-based system for breast cancer classification using fuzzy logic method , 2017, Telematics Informatics.

[87]  Ruslan Salakhutdinov,et al.  Learning Deep Generative Models , 2009 .

[88]  Yoav Shoham,et al.  Multiagent Systems - Algorithmic, Game-Theoretic, and Logical Foundations , 2009 .

[89]  Wenyan Hu,et al.  Online auctions efficiency: a survey of ebay auctions , 2008, WWW.

[90]  Zhaochun Ren,et al.  Explainable Outfit Recommendation with Joint Outfit Matching and Comment Generation , 2018, IEEE Transactions on Knowledge and Data Engineering.

[91]  Po Yang,et al.  Handwritten English Word Recognition Based on Convolutional Neural Networks , 2012, 2012 International Conference on Frontiers in Handwriting Recognition.

[92]  Megha Khosla,et al.  User Fairness in Recommender Systems , 2018, WWW.

[93]  Stephan Hassold,et al.  Public transport vehicle scheduling featuring multiple vehicle types , 2014 .

[94]  Tao Liu,et al.  Synchronization of Public Transport Timetabling with Multiple Vehicle Types , 2016 .

[95]  R. Kwok.  Junior AI researchers are in demand by universities and industry , 2019, Nature.

[96]  Henry Kautz,et al.  Integer optimization models of AI planning problems , 2000, The Knowledge Engineering Review.

[97]  Jeremy A. Marvel,et al.  Technology readiness levels for randomized bin picking , 2012, PerMIS.

[98]  Jesper Simonsen,et al.  Routledge International Handbook of Participatory Design , 2012 .

[99]  Roland Siegwart,et al.  Introduction to Autonomous Mobile Robots , 2004 .

[100]  Sören Kammel,et al.  Bimanual robotic cloth manipulation for laundry folding , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[101]  Adnan Khashman,et al.  Deep Learning in Character Recognition Considering Pattern Invariance Constraints , 2015 .

[102]  Siva R K Narla,et al.  The Evolution of Connected Vehicle Technology: From Smart Drivers to Smart Cars to....Self-Driving Cars. , 2013 .

[103]  Elena R. Messina,et al.  A Framework For Autonomy Levels For Unmanned Systems (ALFUS) , 2005 .

[104]  Jing He,et al.  A Review on Automatic Facial Expression Recognition Systems Assisted by Multimodal Sensor Data , 2019, Sensors.

[105]  Jonathan F. Bard,et al.  Flight Scheduling and Maintenance Base Planning , 1989 .

[106]  David A. Ferrucci,et al.  Introduction to "This is Watson" , 2012, IBM J. Res. Dev..

[107]  Koen V. Hindriks,et al.  The Automated Negotiating Agents Competition, 2010-2015 , 2015, AI Mag..

[108]  Miguel A. Salido,et al.  A Decision Support System for Railway Timetabling (MOM): the Spanish Case , 2006 .

[109]  Demis Hassabis,et al.  Mastering the game of Go without human knowledge , 2017, Nature.

[110]  Pat Langley,et al.  Elements of Machine Learning , 1995 .

[111]  Otthein Herzog,et al.  Text Understanding in Lilog: Integrating Computational Linguistics and Artificial Intelligence Final Report on the IBM Germany Lilog-Project , 1991 .

[112]  Lex Borghans,et al.  The Division of Labour, Worker Organisation, and Technological Change , 2005, SSRN Electronic Journal.

[113]  Xinlei Chen,et al.  Never-Ending Learning , 2012, ECAI.

[114]  Daniel P. W. Ellis,et al.  Speech and Audio Signal Processing - Processing and Perception of Speech and Music, Second Edition , 1999 .

[115]  M. König,et al.  Users’ resistance towards radical innovations: The case of the self-driving car , 2017 .

[116]  Ohbyung Kwon,et al.  Technology acceptance theories and factors influencing artificial Intelligence-based intelligent products , 2020, Telematics Informatics.

[117]  M. Inbar,et al.  CaDet, a computer-based clinical decision support system for early cancer detection. , 1999, Cancer detection and prevention.

[118]  Andeep S. Toor,et al.  Cognitive Computing and the Future of Health Care Cognitive Computing and the Future of Healthcare: The Cognitive Power of IBM Watson Has the Potential to Transform Global Personalized Medicine , 2017, IEEE Pulse.

[119]  R. Spitzer,et al.  The PHQ-9: A new depression diagnostic and severity measure , 2002 .

[120]  Anna Paula Tanajura Ellefsen,et al.  Striving for excellence in AI implementation: AI Maturity Model framework and preliminary research results , 2019, Logforum.

[121]  Michel Gendreau,et al.  A hybrid constraint programming approach to the log-truck scheduling problem , 2011, Ann. Oper. Res..

[122]  Meng Zhang,et al.  Neural Network Methods for Natural Language Processing , 2017, Computational Linguistics.

[123]  Yu He,et al.  The YouTube video recommendation system , 2010, RecSys '10.

[124]  CARLOS A. GOMEZ-URIBE,et al.  The Netflix Recommender System , 2015, ACM Trans. Manag. Inf. Syst..

[125]  José Hernández-Orallo,et al.  A New AI Evaluation Cosmos: Ready to Play the Game? , 2017, AI Mag..

[126]  George Veletsianos.  Cognitive and Affective Benefits of an Animated Pedagogical Agent: Considering Contextual Relevance and Aesthetics , 2007 .

[127]  Mike Preuss,et al.  Planning chemical syntheses with deep neural networks and symbolic AI , 2017, Nature.

[128]  Paul J. Schweitzer,et al.  Assigning buses to schedules in a metropolitan area , 1978, Comput. Oper. Res..

[129]  Yiying Tong,et al.  Age-Invariant Face Recognition , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[130]  Bo Xu,et al.  Image character recognition using deep convolutional neural network learned from different languages , 2014, 2014 IEEE International Conference on Image Processing (ICIP).

[131]  Marc G. Bellemare,et al.  The Arcade Learning Environment: An Evaluation Platform for General Agents , 2012, J. Artif. Intell. Res..