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Ole-Christoffer Granmo

Professor

Director, Centre for Artificial Intelligence Research (CAIR)

 
Office:
A3062 ( Jon Lilletuns vei 9, Grimstad )

Professor Ole-Christoffer Granmo is Director of the Centre for Artificial Intelligence Research (CAIR). His passion for artificial intelligence was lit at the age of ten when he got his first computer and discovered programming. Fascinated by the idea of superintelligence, he obtained his master's degree in informatics in 1999 and the PhD degree in 2004, both from the University of Oslo, Norway. Granmo develops theory and algorithms for systems that explore, experiment and learn in complex real-world environments. Drawing inspiration from the paradigms of deep reinforcement learning and probabilistic causal reasoning, he seeks to surpass human capability in flexible pattern recognition, model building and reasoning. Within his field of research, Granmo has written more than 115 refereed journal and conference publications.

Google Scholar Profile

Projects

PhD Students

Scientific publications

  • Zhang, Xuan; Jiao, Lei; Oommen, John; Granmo, Ole-Christoffer (2019). A Conclusive Analysis of the Finite-Time Behavior of the Discretized Pursuit Learning Automaton. IEEE Transactions on Neural Networks and Learning Systems. ISSN: 2162-237X. doi:10.1109/TNNLS.2019.2900639.
  • Abeyrathna, Kuruge Darshana; Granmo, Ole-Christoffer; Zhang, Xuan; Goodwin, Morten (2019). A Scheme for Continuous Input to the Tsetlin Machine with Applications to Forecasting Disease Outbreaks. Advances and Trends in Artificial Intelligence. From Theory to Practice.. ISBN: 978-3-030-22999-3. Springer Nature. 978-3-030-22999-3.
  • Matheussen, Bernt Viggo; Granmo, Ole-Christoffer; Sharma, Jivitesh (2019). Hydropower optimization using deep learning. Lecture Notes in Computer Science. ISSN: 0302-9743. 11606 LNAIs 110 - 122. doi:10.1007/978-3-030-22999-3_11.
  • Abeyrathna, Kuruge Darshana; Granmo, Ole-Christoffer; Lei, Jiao; Goodwin, Morten (2019). The Regression Tsetlin Machine: A Tsetlin Machine for Continuous Output Problems. Progress in Artificial Intelligence. EPIA 2019. ISBN: 978-3-030-30244-3. Springer. chapter.
  • Glimsdal, Sondre; Granmo, Ole-Christoffer (2019). Thompson sampling based active learning in probabilistic programs with application to travel time estimation. Lecture Notes in Computer Science. ISSN: 0302-9743. 11606 LNAIs 71 - 78. doi:10.1007/978-3-030-22999-3_7.
  • Glimsdal, Sondre; Granmo, Ole-Christoffer (2018). A Bayesian network based solution scheme for the constrained Stochastic On-line Equi-Partitioning Problem. Applied intelligence (Boston). ISSN: 0924-669X. 48s 3735 - 3747. doi:10.1007/s10489-018-1172-8.
  • Abeyrathna, Kuruge Darshana; Granmo, Ole-Christoffer; Goodwin, Morten (2018). A Novel Tsetlin Automata Scheme to Forecast Dengue Outbreaks in the Philippines. Proceedings - International Conference on Tools with Artificial Intelligence (ICTAI). ISSN: 1082-3409. 2018-Novembers 680 - 685. doi:10.1109/ICTAI.2018.00108.
  • Sharma, Jivitesh; Granmo, Ole-Christoffer; Goodwin, Morten (2018). Deep CNN-ELM Hybrid Models for Fire Detection in Images. Lecture Notes in Computer Science. ISSN: 0302-9743. LNCS 11141s 245 - 259. doi:10.1007/978-3-030-01424-7_25.
  • Andersen, Per-Arne; Goodwin, Morten; Granmo, Ole-Christoffer (2018). Deep RTS: A Game Environment for Deep Reinforcement Learning in Real-Time Strategy Games. 2018 IEEE Conference on Computational Intelligence and Games (CIG). ISBN: 978-1-5386-4359-4. IEEE conference proceedings. chapter.
  • Abeyrathna, Kuruge Darshana; Granmo, Ole-Christoffer; Goodwin, Morten (2018). Effect of Data from Neighbouring Regions to Forecast Dengue Incidences in Different Regions of Philippines Using Artificial Neural Networks. NIK: Norsk Informatikkonferanse. ISSN: 1892-0713.
  • Havelock, Jessica; Oommen, John; Granmo, Ole-Christoffer (2018). Novel Distance Estimation Methods Using 'Stochastic Learning on the Line' Strategies. IEEE Access. ISSN: 2169-3536. 6s 48438 - 48454. doi:10.1109/ACCESS.2018.2868233.
  • Havelock, Jessica; Oommen, John; Granmo, Ole-Christoffer (2018). On using "Stochastic learning on the line" to design novel distance estimation methods. Lecture Notes in Computer Science. ISSN: 0302-9743. 10868 LNAIs 34 - 42. doi:10.1007/978-3-319-92058-0_4.
  • Razvarz, Sina; Jafari, Raheleh; Granmo, Ole-Christoffer; Gegov, Alexander (2018). Solution of Dual Fuzzy Equations Using a New Iterative Method. Intelligent Information and Database Systems - 10th Asian Conference, ACIIDS 2018, Dong Hoi City, Vietnam, March 19-21, 2018, Proceedings, Part II. ISBN: 978-3-319-75419-2. Springer. chapter. s 245 - 255.
  • Andersen, Per-Arne; Goodwin, Morten; Granmo, Ole-Christoffer (2018). The dreaming variational autoencoder for reinforcement learning environments. Lecture Notes in Computer Science. ISSN: 0302-9743. 11311 LNAIs 143 - 155. doi:10.1007/978-3-030-04191-5_11.
  • Kamphaug, Åsmund; Granmo, Ole-Christoffer; Goodwin, Morten; Zadorozhny, Vladimir (2018). Towards Open Domain Chatbots — A GRU Architecture for Data Driven Conversations. Internet Science - INSCI 2017 International Workshops IFIN, DATA ECONOMY, DSI, and CONVERSATIONS - LNCS10750. ISBN: 978-3-319-77546-3. Springer Nature. Workshop paper. s 2013 - 2022.
  • Fidje, Jahn Thomas; Granmo, Ole-Christoffer; Haraldseid, Christian Kråkevik; Goodwin, Morten; Matheussen, Bernt Viggo (2017). A Learning Automata Local Contribution Sampling Applied to Hydropower Production Optimisation. Artificial Intelligence XXXIV: 37th SGAI International Conference on Artificial Intelligence, AI 2017, Cambridge, UK, December 12-14, 2017, Proceedings. ISBN: 978-3-319-71077-8. Springer Publishing Company. Artikkel.
  • Berge, Geir Thore; Granmo, Ole-Christoffer; Tveit, Tor Oddbjørn (2017). Combining Unsupervised, Supervised, and Rule-based Algorithms for Text Mining of Electronic Health Records-A Clinical Decision Support System for Identifying and Classifying Allergies of Concern for Anesthesia During Surgery. Information Systems Development: Advances in Methods, Tools and Management (ISD2017 Proceedings). ISBN: 978-9963-2288-3-6. Association for Information Systems. KAPITTEL.
  • Sharma, Jivitesh; Granmo, Ole-Christoffer; Goodwin, Morten; Fidje, Jahn Thomas (2017). Deep convolutional neural networks for fire detection in images. Communications in Computer and Information Science. ISSN: 1865-0929. 744s 183 - 193. doi:10.1007/978-3-319-65172-9_16.
  • Andersen, Per-Arne; Goodwin, Morten; Granmo, Ole-Christoffer (2017). FlashRL: A Reinforcement Learning Platform for Flash Games. NIK: Norsk Informatikkonferanse. ISSN: 1892-0713.
  • Andersen, Per-Arne; Goodwin, Morten; Granmo, Ole-Christoffer (2017). Towards a deep reinforcement learning approach for tower line wars. Lecture Notes in Computer Science. ISSN: 0302-9743. 10630 LNAIs 101 - 114. doi:10.1007/978-3-319-71078-5_8.
  • Lazreg, Mehdi Ben; Goodwin, Morten; Granmo, Ole-Christoffer (2017). Vector Representation of Non-standard Spellings Using Dynamic Time Wrapping and a Denoising Autoencoder. 2017 IEEE Congress on Evolutionary Computation (CEC). ISBN: 978-1-5090-4601-0. IEEE conference proceedings. chapter. s 1444 - 1450.
  • Granmo, Ole-Christoffer (2016). Bayesian Unification of Gradient and Bandit-Based Learning for Accelerated Global Optimisation. 2016 15th IEEE International Conference on Machine Learning and Applications. ISBN: 978-1-5090-6166-2. IEEE conference proceedings. chapter. s 222 - 226.
  • Lazreg, Mehdi Ben; Goodwin, Morten; Granmo, Ole-Christoffer (2016). Deep Learning for Social Media Analysis in Crises Situations. The 29th Annual Workshop of the Swedish Artificial Intelligence Society (SAIS). ISBN: 978-91-7685-720-5. Linköping University Electronic Press. Kapittel. s 31 - 36.
  • Lazreg, Mehdi Ben; Goodwin, Morten; Granmo, Ole-Christoffer (2016). Information abstraction from crises related tweets using recurrent neural network. IFIP Advances in Information and Communication Technology. ISSN: 1868-4238. 475s 441 - 452. doi:10.1007/978-3-319-44944-9_38.
  • Lei, Jiao; Zhang, Xuan; Oommen, John; Granmo, Ole-Christoffer (2016). Optimizing channel selection for cognitive radio networks using a distributed Bayesian learning automata-based approach. Applied intelligence (Boston). ISSN: 0924-669X. 44 (2). s 307 - 321. doi:10.1007/s10489-015-0682-x.
  • Yazidi, Anis; Oommen, John; Horn, Geir Henrik; Granmo, Ole-Christoffer (2016). Stochastic discretized learning-based weak estimation: a novel estimation method for non-stationary environments. Pattern Recognition. ISSN: 0031-3203. 60s 430 - 443. doi:10.1016/j.patcog.2016.05.001.
  • Zhang, Xuan; Oommen, John; Granmo, Ole-Christoffer (2016). The design of absorbing Bayesian pursuit algorithms and the formal analyses of their ε-optimality. Pattern Analysis and Applications. ISSN: 1433-7541. s 1 - 12. doi:10.1007/s10044-016-0535-1.
  • Hansen, Bjørnar; Loland, Leonard Christopher; Goodwin, Morten; Granmo, Ole-Christoffer (2016). Towards Evacuation Planning of Groups with Genetic Algorithms. The 29th Annual Workshop of the Swedish Artificial Intelligence Society (SAIS). ISBN: 978-91-7685-720-5. Linköping University Electronic Press. 3. s 20 - 30.
  • Lazreg, Mehdi Ben; Radianti, Jaziar; Granmo, Ole-Christoffer (2015). A Bayesian network model for fire assessment and prediction. Lecture Notes in Computer Science. ISSN: 0302-9743. 9432s 269 - 279. doi:10.1007/978-3-319-27926-8_24.
  • Zhang, Xuan; Oommen, John; Granmo, Ole-Christoffer; Lei, Jiao (2015). A formal proof of the e-optimality of discretized pursuit algorithms. Applied intelligence (Boston). ISSN: 0924-669X. doi:10.1007/s10489-015-0670-1.
  • Radianti, Jaziar; Granmo, Ole-Christoffer; Bouhmala, Noureddine; Sarshar, Parvaneh; Gonzalez, Jose J (2015). Comparing Different Crowd Emergency Evacuation Models Based on Human Centered Sensing Criteria. International Journal of Information Systems for Crisis Response and Management. ISSN: 1937-9390. 6 (3). s 53 - 70. doi:10.4018/IJISCRAM.2014070104.
  • Radianti, Jaziar; Lazreg, Mehdi Ben; Granmo, Ole-Christoffer (2015). Fire simulation-based adaptation of SmartRescue App for serious game: Design, setup and user experience. Engineering applications of artificial intelligence. ISSN: 0952-1976. 46s 312 - 325. doi:10.1016/j.engappai.2015.06.012.
  • Matheussen, Bernt Viggo; Granmo, Ole-Christoffer (2015). Modeling snow dynamics using a bayesian network. Lecture Notes in Computer Science. ISSN: 0302-9743. 9101s 382 - 393. doi:10.1007/978-3-319-19066-2_37.
  • Lazreg, Mehdi Ben; Radianti, Jaziar; Granmo, Ole-Christoffer (2015). SmartRescue: Architecture for Fire Crisis Assessment and Prediction. 12th International Conference on Information Systems for Crisis Response and Management. ISBN: 978-82-7117-788-1. ISCRAM. Chapter.
  • Glimsdal, Sondre; Granmo, Ole-Christoffer (2015). Thompson Sampling Guided Stochastic Searching on the Line for Non-Stationary Adversarial Learning. 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA). ISBN: 978-1-5090-0287-0. IEEE. Kapittel. s 687 - 692.
  • Glimsdal, Sondre; Granmo, Ole-Christoffer (2015). Thompson sampling guided stochastic searching on the line for adversarial learning. IFIP Advances in Information and Communication Technology. ISSN: 1868-4238. 458s 307 - 317. doi:10.1007/978-3-319-23868-5_22.
  • Webersik, Christian; Gonzalez, Jose J; Dugdale, Julie Anne; Munkvold, Bjørn Erik; Granmo, Ole-Christoffer (2015). Towards an integrated approach to emergency management: interdisciplinary challenges for research and practice. Culture Unbound. Journal of Current Cultural Research. ISSN: 2000-1525. 7 (3). s 524 - 540. doi:10.3384/cu.2000.1525.1572525.
  • Lei, Jiao; Zhang, Xuan; Granmo, Ole-Christoffer; Oommen, John (2014). A Bayesian Learning Automata-Based Distributed Channel Selection Scheme. Modern Advances in Applied Intelligence, 27th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2014,Kaohsiung, Taiwan, June 3-6, 2014, Part II. ISBN: 978-3-319-07455-9. Springer. kapittel. s 48 - 57.
  • Radianti, Jaziar; Granmo, Ole-Christoffer (2014). A Framework for Assessing the Condition of Crowds Exposed to a Fire Hazard Using a Probabilistic Model. International Journal of Machine Learning and Computing. ISSN: 2010-3700. 4 (1). s 14 - 20. doi:10.7763/IJMLC.2014.V4.379.
  • Glimsdal, Sondre; Granmo, Ole-Christoffer (2014). A Novel Bayesian Network Based Scheme for Finding the Optimal Solution to Stochastic Online Equi-partitioning Problems. 2014 13th International Conference on Machine Learning and Applications (ICMLA). ISBN: 978-1-4799-7415-3. IEEE conference proceedings. kapittel. s 594 - 599.
  • Zhang, Xuan; Granmo, Ole-Christoffer; Oommen, John; Lei, Jiao (2014). A formal proof of the ε-optimality of absorbing continuous pursuit algorithms using the theory of regular functions. Applied intelligence (Boston). ISSN: 0924-669X. 41 (3). s 974 - 985. doi:10.1007/s10489-014-0541-1.
  • Yazidi, Anis; Granmo, Ole-Christoffer; Oommen, John; Goodwin, Morten (2014). A novel strategy for solving the stochastic point location problem using a hierarchical searching scheme. IEEE Transactions on Cybernetics. ISSN: 2168-2267. 44 (11). s 2202 - 2220. doi:10.1109/TCYB.2014.2303712.
  • Radianti, Jaziar; Granmo, Ole-Christoffer; Sarshar, Parvaneh; Goodwin, Morten; Dugdale, Julie Anne; Gonzalez, Jose J (2014). A spatio-temporal probabilistic model of hazard- and crowd dynamics for evacuation planning in disasters. Applied intelligence (Boston). ISSN: 0924-669X. 42 (1). s 3 - 23. doi:10.1007/s10489-014-0583-4.
  • Haugland, Vegard; Kjølleberg, Marius; Larsen, Svein-Erik; Granmo, Ole-Christoffer (2014). A two-armed bandit collective for hierarchical examplar based mining of frequent itemsets with applications to intrusion detection. Transactions on Computational Collective Intelligence XIV. ISBN: 9783662445099. Springer. kapittel.
  • Gupta, Neha; Granmo, Ole-Christoffer; Agrawala, Ashok (2014). Arm Space Decomposition as a Strategy for Tackling Large Scale Multi-Armed Bandit Problems. 2013 12th International Conference on Machine Learning and Applications (ICMLA 2013). ISBN: 9781479941551. Curran Associates, Inc.. kapittel. s 252 - 257.
  • Goodwin, Morten; Granmo, Ole-Christoffer; Radianti, Jaziar (2014). Escape planning in realistic fire scenarios with Ant Colony Optimisation. Applied intelligence (Boston). ISSN: 0924-669X. 42 (1). s 24 - 35. doi:10.1007/s10489-014-0538-9.
  • Yazidi, Anis; Oommen, John; Granmo, Ole-Christoffer; Goodwin, Morten (2014). On Utilizing Stochastic Non-linear Fractional Bin Packing to Resolve Distributed Web Crawling. 17th IEEE International Conference on Computational Science and Engineering, CSE 2014. ISBN: 978-1-4799-7981-3. IEEE conference proceedings. kapittel. s 32 - 37.
  • Radianti, Jaziar; Gonzalez, Jose J; Granmo, Ole-Christoffer (2014). Publish-subscribe smartphone sensing platform for the acute phase of a disaster: A framework for emergency management support. 2014 IEEE International Conference on Pervasive Computing and Communication Workshops (PERCOM WORKSHOPS 2014). ISBN: 978-1-4799-2737-1. Curran Associates, Inc.. kapittel. s 285 - 290.
  • Radianti, Jaziar; Dugdale, Julie Anne; Gonzalez, Jose J; Granmo, Ole-Christoffer (2014). Smartphone sensing platform for emergency management. Proceedings ISCRAM2014 , 11th International Conference on Information Systems for Crisis Response and Management. ISBN: 978-0-692-21194-6. The Pennsylvania State University. kapittel. s 379 - 383.
  • Zhang, Xuan; Oommen, John; Granmo, Ole-Christoffer; Lei, Jiao (2014). Using the Theory of Regular Functions to Formally Prove the ε -Optimality of Discretized Pursuit Learning Algorithms. Modern Advances in Applied Intelligence - 27th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2014, Kaohsiung, Taiwan, June 3-6, 2014, Proceedings, Part I. ISBN: 978-3-319-07467-2. Springer. kapittel. s 379 - 388.
  • Sarshar, Parvaneh; Radianti, Jaziar; Granmo, Ole-Christoffer; Gonzalez, Jose J (2013). A Bayesian Network Model for Evacuation Time Analysis During a Ship Fire. 2013 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE). ISBN: 9781467358491. IEEE conference proceedings. kapittel. s 100 - 107.
  • Sarshar, Parvaneh; Radianti, Jaziar; Granmo, Ole-Christoffer; Gonzalez, Jose J (2013). A Dynamic Bayesian Network Model for Predicting Congestion During a Ship Fire Evacuation. Proceedings of The World Congress on Engineering and Computer Science (WCECS) 2013 : Vol I. ISBN: 978-988-19252-3-7. International Association of Engineers. kapittel.
  • Granmo, Ole-Christoffer; Radianti, Jaziar; Goodwin, Morten; Dugdale, Julie Anne; Sarshar, Parvaneh; Glimsdal, Sondre; Gonzalez, Jose J (2013). A Spatio-Temporal Probabilistic Model of Hazard and Crowd Dynamics in Disasters for Evacuation Planning. Recent Trends in Applied Artificial Intelligence. ISBN: 978-3-642-38576-6. Springer. kapittel. s 63 - 72.
  • Granmo, Ole-Christoffer; Glimsdal, Sondre (2013). Accelerated Bayesian learning for decentralized two-armed bandit based decision making with applications to the Goore Game. Applied intelligence (Boston). ISSN: 0924-669X. 38 (4). s 479 - 488. doi:10.1007/s10489-012-0346-z.
  • Goodwin, Morten; Granmo, Ole-Christoffer; Radianti, Jaziar; Sarshar, Parvaneh; Glimsdal, Sondre (2013). Ant Colony Optimisation for Planning Safe Escape Routes. Recent Trends in Applied Artificial Intelligence. ISBN: 978-3-642-38576-6. Springer. kapittel. s 53 - 62.
  • Zhang, Xuan; Lei, Jiao; Granmo, Ole-Christoffer; Oommen, John (2013). Channel selection in cognitive radio networks: A switchable Bayesian learning automata approach. 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC). ISBN: 978-1-4673-6234-4. IEEE conference proceedings. kapittel. s 2362 - 2367.
  • Radianti, Jaziar; Granmo, Ole-Christoffer; Bouhmala, Nourddine; Sarshar, Parvaneh; Yazidi, Anis; Gonzalez, Jose J (2013). Crowd Models for Emergency Evacuation: A Review Targeting Human-Centered Sensing. 46th Hawaii International Conference on System Sciences (HICSS). ISBN: 978-1-4577-1925-7. IEEE. kapittel. s 156 - 165.
  • Yazidi, Anis; Granmo, Ole-Christoffer; Oommen, John (2013). Learning-Automaton-Based Online Discovery and Tracking of Spatiotemporal Event Patterns. IEEE Transactions on Cybernetics. ISSN: 2168-2267. 43 (3). s 1118 - 1130. doi:10.1109/TSMCB.2012.2224339.
  • Zhang, Xuan; Granmo, Ole-Christoffer; Oommen, John; Lei, Jiao (2013). On Using the Theory of Regular Functions to Prove the Epsilon-Optimality of the Continuous Pursuit Learn- ing Automaton. Recent Trends in Applied Artificial Intelligence. ISBN: 978-3-642-38576-6. Springer. kapittel. s 262 - 271.
  • Zhang, Xuan; Granmo, Ole-Christoffer; Oommen, John (2013). On incorporating the paradigms of discretization and Bayesian estimation to create a new family of pursuit learning automata. Applied intelligence (Boston). ISSN: 0924-669X. 39 (4). s 782 - 792. doi:10.1007/s10489-013-0424-x.
  • Stensby, Aleksander; Granmo, Ole-Christoffer; Oommen, John (2013). The use of weak estimators to achieve language detection and tracking in multilingual documents. International journal of pattern recognition and artificial intelligence. ISSN: 0218-0014. 27 (4). doi:10.1142/S0218001413500110.
  • Yazidi, Anis; Granmo, Ole-Christoffer; Oommen, John; Goodwin, Morten (2012). A Hierarchical Learning Scheme for Solving the Stochastic Point Location Problem. Advanced Research in Applied Artificial Intelligence : 25th International Conference 25th International Conference on Industrial Engineering and OtherApplications of Applied Intelligent Systems, IEA/AIE 2012 Dalian, China, June 9-12, 2012 Proceedings. ISBN: 978-3-642-31086-7. Springer. Kapittel. s 774 - 783.
  • Yazidi, Anis; Oommen, John; Granmo, Ole-Christoffer (2012). A Novel Stochastic Discretized Weak Estimator Operating in Non-Stationary Environments. 2012 International Conference on Computing, Networking and Communications (ICNC). ISBN: 978-1-4673-0009-4. IEEE Communications Society. Kapittel. s 364 - 370.
  • Yazidi, Anis; Granmo, Ole-Christoffer; Oommen, John (2012). A Stochastic Search on the Line-Based Solution to Discretized Estimation. Advanced Research in Applied Artificial Intelligence : 25th International Conference 25th International Conference on Industrial Engineering and OtherApplications of Applied Intelligent Systems, IEA/AIE 2012 Dalian, China, June 9-12, 2012 Proceedings. ISBN: 978-3-642-31086-7. Springer. Kapittel. s 764 - 773.
  • Granmo, Ole-Christoffer; Oommen, John; Pedersen, Asle (2012). Achieving Unbounded Resolution in Finite Player Goore Games Using Stochastic Automata, and Its Applications. Sequential Analysis. ISSN: 0747-4946. 31 (2). s 190 - 218. doi:10.1080/07474946.2012.665685.
  • Oommen, John; Yazidi, Anis; Granmo, Ole-Christoffer (2012). An Adaptive Approach to Learning the Preferences of Users in a Social Network Using Weak Estimators. Journal of Information Processing Systems. ISSN: 1976-913X. 8 (2). s 191 - 212. doi:10.3745/JIPS.2012.8.2.191.
  • Zhang, Xuan; Granmo, Ole-Christoffer; Oommen, John (2012). Discretized Bayesian Pursuit – A New Scheme for Reinforcement Learning. Advanced Research in Applied Artificial Intelligence : 25th International Conference 25th International Conference on Industrial Engineering and OtherApplications of Applied Intelligent Systems, IEA/AIE 2012 Dalian, China, June 9-12, 2012 Proceedings. ISBN: 978-3-642-31086-7. Springer. Kapittel. s 784 - 793.
  • Yazidi, Anis; Granmo, Ole-Christoffer; Oommen, John (2012). Service selection in stochastic environments: a learning-automaton based solution. Applied intelligence (Boston). ISSN: 0924-669X. 36 (3). s 617 - 637. doi:10.1007/s10489-011-0280-5.
  • Yazidi, Anis; Granmo, Ole-Christoffer; Oommen, John (2011). A New Tool for the Modeling of AI and Machine Learning Applications: Random Walk-Jump Processes. Hybrid Artificial Intelligent Systems: 6th International Conference, HAIS 2011, Wroclaw, Poland, May 23-25, 2011, Proceedings, Part I. ISBN: 978-3642212185. Springer. Kapittel. s 11 - 21.
  • Granmo, Ole-Christoffer; Glimsdal, Sondre (2011). A Two-Armed Bandit Based Scheme for Accelerated Decentralized Learning. Modern Approaches in Applied Intelligence24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011, Syracuse, NY, USA, June 28 – July 1, 2011, Proceedings, Part II. ISBN: 978-3-642-21826-2. Springer. Kapittel. s 532 - 541.
  • Haugland, Vegard; Kjølleberg, Marius; Larsen, Svein-Erik; Granmo, Ole-Christoffer (2011). A Two-Armed Bandit Collective for Examplar Based Mining of Frequent Itemsets with Applications to Intrusion Detection. Lecture Notes in Computer Science. ISSN: 0302-9743. 6922s 72 - 81.
  • Haugland, Vegard; Kjølleberg, Marius; Larsen, Svein-Erik; Granmo, Ole-Christoffer (2011). A Two-Armed Bandit Collective for Examplar Based Mining of Frequent Itemsets with Applications to Intrusion Detection. Computational Collective Intelligence.Technologies and Applications. Third International Conference, ICCCI 2011 Gdynia, Poland, September 21-23, 2011 Proceedings, Part I. ISBN: 978-3-642-23934-2. Springer. Kapittel. s 72 - 81.
  • Yazidi, Anis; Granmo, Ole-Christoffer; Oommen, John; Gerdes, Martin; Reichert, Frank (2011). A User-Centric Approach for Personalized Service Provisioning in Pervasive Environments. Wireless personal communications. ISSN: 0929-6212. 61 (3). s 543 - 566. doi:10.1007/s11277-011-0387-3.
  • Yazidi, Anis; Granmo, Ole-Christoffer; Oommen, John; Reichert, Frank; Gerdes, Martin (2011). An Intelligent Architecture for Service Provisioning in Pervasive Environments. Proceedings, 2011 International Symposium on Innovations in Intelligent Systems and Applications (INISTA'11). ISBN: 978-1-61284-919-5. IEEE conference proceedings. Kapittel. s 524 - 530.
  • Bouhmala, Nourddine; Granmo, Ole-Christoffer (2011). GSAT Enhanced with Learning Automata and Multilevel Paradigm. International Journal of Computer Science Issues. ISSN: 1694-0784. 8 (6). s 38 - 54.
  • Zhang, Xuan; Oommen, John; Granmo, Ole-Christoffer (2011). Generalized Bayesian Pursuit: A Novel Scheme for Multi-Armed Bernoulli Bandit Problems. Artificial Intelligence Applications and Innovations 12th INNS EANN-SIG International Conference,EANN2011 and 7th IFIP WG 12.5 International Conference, AIAI 2011 Corfu, Greece, September 15-18, 2011 Proceedings , Part II. ISBN: 978-3-642-23959-5. Springer. Artikkel. s 122 - 131.
  • Zhang, Xuan; Oommen, John; Granmo, Ole-Christoffer (2011). Generalized Bayesian pursuit: a novel scheme for multi-armed Bernoulli bandit problems. IFIP Advances in Information and Communication Technology. ISSN: 1868-4238. 364s 122 - 131.
  • Granmo, Ole-Christoffer; Oommen, John (2011). Learning automata-based solutions to the optimal web polling problem modelled as a nonlinear fractional knapsack problem. Engineering applications of artificial intelligence. ISSN: 0952-1976. 24 (7). s 1238 - 1251. doi:10.1016/j.engappai.2011.05.018.
  • Yazidi, Anis; Granmo, Ole-Christoffer; Oommen, John (2011). ON THE ANALYSIS OF A NEW MARKOV CHAIN WHICH HAS APPLICATIONS IN AI AND MACHINE LEARNING. Proceedings, 24th Canadian conference on electrical and computer engineering (CCECE 2011). ISBN: 9781424497898. IEEE conference proceedings. Kapittel. s 1553 - 1558.
  • Yazidi, Anis; Granmo, Ole-Christoffer; Oommen, John (2011). On the Analysis of a RandomInterleaving Walk-Jump Process with Applications to Testing. Sequential Analysis. ISSN: 0747-4946. 30 (4). s 457 - 478. doi:10.1080/07474946.2011.619104.
  • Gupta, Neha; Granmo, Ole-Christoffer; Agrawala, Ashok (2011). Successive Reduction of Arms in Multi-Armed Bandits. Research and Development in Intelligent Systems. ISBN: 9781447123187. Springer. Artikkel. s 181 - 194.
  • Zhang, Xuan; Granmo, Ole-Christoffer; Oommen, John (2011). The Bayesian Pursuit Algorithm: A New Family of Estimator Learning Automata. Modern Approaches in Applied Intelligence24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011, Syracuse, NY, USA, June 28 – July 1, 2011, Proceedings, Part II. ISBN: 978-3-642-21826-2. Springer. KAPITTEL. s 522 - 531.
  • Gupta, Neha; Granmo, Ole-Christoffer; Agrawala, Ashok (2011). Thompson Sampling for Dynamic Multi-armed Bandits. 2011 10th International Conference on Machine Learning and Applications and Workshops. ISBN: 9780769546070. IEEE. Artikkel. s 484 - 489.
  • Yazidi, Anis; Granmo, Ole-Christoffer; Oommen, John (2011). Tracking the Preferences of Users Using Weak Estimators. AI 2011: Advances in Artificial Intelligence. 24th Australasian Joint Conference Perth, Australia, December 5-8, 2011. Proceedings. ISBN: 978-3-642-25831-2. Springer. Kapittel. s 799 - 808.
  • Norheim, Thomas; Brådland, Terje; Granmo, Ole-Christoffer; Oommen, John (2010). A Generic Solution to Multi-Armed Bernoulli Bandit Problems Based on Random Sampling from Sibling Conjugate Priors. ICAART 2010, 2nd International Conference on Agents and Artificial Intelligence, Proceedings. ISBN: 978-989-674-021-4. Institute for Systems and Technologies of Information, Control and Communication. kap. s 36 - 44.
  • Yazidi, Anis; Granmo, Ole-Christoffer; Oommen, John (2010). A Learning Automata Based Solution to Service Selection in Stochastic Environments. Lecture Notes in Computer Science. ISSN: 0302-9743. (6098). s 209 - 218. doi:10.1007/978-3-642-13033-5_22.
  • Granmo, Ole-Christoffer; Bouhmala, Nourddine (2010). Enhancing Local-search based SAT Solvers with Learning Capability. ICAART 2010, 2nd International Conference on Agents and Artificial Intelligence, Proceedings. ISBN: 978-989-674-021-4. Institute for Systems and Technologies of Information, Control and Communication. paper. s 515 - 521.
  • Stensby, Aleksander; Oommen, John; Granmo, Ole-Christoffer (2010). Language Detection and Tracking in Multilingual Documents Using Weak Estimators. Lecture Notes in Computer Science. ISSN: 0302-9743. 6218s 600 - 609.
  • Yazidi, Anis; Granmo, Ole-Christoffer; Lin, M.; Wen, X; Oommen, John; Gerdes, Martin; Reichert, Frank (2010). Learning Automaton Based On-Line Discovery and Tracking of Spatio-temporal Event Patterns. Lecture Notes in Computer Science. ISSN: 0302-9743. 6230s 327 - 338.
  • Granmo, Ole-Christoffer; Oommen, John (2010). Optimal sampling for estimation with constrained resources using a learning automaton-based solution for the nonlinear fractional knapsack problem. Applied intelligence (Boston). ISSN: 0924-669X. 33 (1). s 3 - 20. doi:10.1007/s10489-010-0228-1.
  • Granmo, Ole-Christoffer; Berg, Stian (2010). Solving Non-Stationary Bandit Problems by Random Sampling from Sibling Kalman Filters. Lecture Notes in Computer Science. ISSN: 0302-9743. 6098s 199 - 208.
  • Granmo, Ole-Christoffer; Granmo, Ole Christoffer; Oommen, John (2010). Solving Stochastic Nonlinear Resource Allocation Problems Using a Hierarchy of Twofold Resource Allocation Automata. IEEE transactions on computers. ISSN: 0018-9340. 59 (4). s 545 - 560. doi:10.1109/TC.2009.189.
  • Granmo, Ole-Christoffer (2010). Solving Two-Armed Bernoulli Bandit Problems Using a Bayesian Learning Automaton. International Journal of Intelligent Computing and Cybernetics. ISSN: 1793-5423. 3 (2). s 207 - 234.
  • Bouhmala, Noureddine; Granmo, Ole-Christoffer (2010). Stochastic Learning for SAT- Encoded Graph Coloring Problems. International Journal of Applied Metaheuristic Computing. ISSN: 1947-8283. 1 (3). s 1 - 19. doi:10.4018/jamc.2010070101.
  • Granmo, Ole-Christoffer; Bouhmala, Nourddine (2010). Using Learning Automata to Enhance Local-Search Based SAT Solvers with Learning Capability. Application of Machine Learning. ISBN: 978-953-307-035-3. IntechOpen. 5. s 63 - 85.
  • Granmo, Ole-Christoffer; Oommen, B. John (2009). A Hierarchy of Twofold Resource Allocation Automata Supporting Optimal Sampling. Next-Generation Applied Intelligence : 22nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2009, Tainan, Taiwan, June 24-27, 2009. Proceedings. Springer. s 523 - 534.
  • Oommen, B. John; Granmo, Ole-Christoffer; Liang, Z. (2009). A Novel Multidimensional Scaling Technique for Mapping Word-Of-Mouth Discussions. Opportunities and Challenges for next Generation Applied Intelligence. ISBN: 978-3-540-92813-3. Springer.
  • Granmo, Ole-Christoffer; Oommen, B. John (2009). Learning Automata-based Solutions to Stochastic Nonlinear Resource Allocation Problems. Intelligent Systems for Knowledge Management. ISBN: 9783642041693. Springer. s 1 - 30.
  • Oommen, B. John; Granmo, Ole-Christoffer (2009). Learning automata-based solutions to the Goore game and its applications. Game theory: strategies, equilibria, and theorems. ISBN: 978-1-604-56844-8. Nova Science Publishers, Inc.. s 183 - 216.
  • Granmo, Ole-Christoffer (2009). The Bayesian Learning Automaton - Empirical Evaluation with Two-Armed Bernoulli Bandit Problems. Proceedings of AI-2008, The Twenty-eight SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence. ISBN: 9781848822146. Springer. s 235 - 248.
  • Granmo, Ole-Christoffer (2019). Tekstmining i dagliglivet.
  • Goodwin, Morten; Granmo, Ole-Christoffer; Larsen, Arne Martin (2019). Fikk råd om kunstig intelligens https://www.nora.ai/news-and-events/news/fikk-rad-om-kunstig-intelligens.html.
  • Goodwin, Morten; Granmo, Ole-Christoffer; Larsen, Arne Martin (2019). Fikk råd om kunstig intelligens.
  • Granmo, Ole-Christoffer; Goodwin, Morten; Karlsen, Kjetil (2019). Kunstig intelligens gir store muligheter.
  • Granmo, Ole-Christoffer; Ihme, Henrik (2019). Vil bli best på kunstig intelligens.
  • Granmo, Ole-Christoffer; Christiansen, Atle (2019). Når kunstig intelligens vet hva du feiler om et halvt års tid.

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