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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

  • Abeyrathna, Kuruge Darshana; Granmo, Ole-Christoffer; Goodwin, Morten (2021). Adaptive sparse representation of continuous input for tsetlin machines based on stochastic searching on the line. Electronics. ISSN: 2079-9292. 10 (17). doi:10.3390/electronics10172107.
  • Abeyrathna, Kuruge Darshana; Granmo, Ole-Christoffer; Goodwin, Morten (2021). Extending the Tsetlin Machine With Integer-Weighted Clauses for Increased Interpretability. IEEE Access. ISSN: 2169-3536. 9s 8233 - 8248. doi:10.1109/ACCESS.2021.3049569.
  • Yadav, Rohan Kumar; Lei, Jiao; Granmo, Ole-Christoffer; Goodwin, Morten (2021). Interpretability in Word Sense Disambiguation using Tsetlin Machine. Proceedings of the 13th International Conference on Agents and Artificial Intelligence (ICAART 2021). ISBN: 978-989-758-484-8. SciTePress. chapter. s 402 - 409.
  • Abouzeid, Ahmed Abdulrahem Othman; Granmo, Ole-Christoffer; Webersik, Christian; Goodwin, Morten (2021). Learning Automata-based Misinformation Mitigation via Hawkes Processes. Information Systems Frontiers. ISSN: 1387-3326. doi:10.1007/s10796-020-10102-8.
  • Bhattarai, Bimal; Granmo, Ole-Christoffer; Jiao, Lei (2021). Measuring the Novelty of Natural Language Text using the Conjunctive Clauses of a Tsetlin Machine Text Classifier. Proceedings of the 13th International Conference on Agents and Artificial Intelligence (ICAART 2021). ISBN: 978-989-758-484-8. SciTePress.
  • Zhang, Xuan; Lei, Jiao; Granmo, Ole-Christoffer; Goodwin, Morten (2021). On the Convergence of Tsetlin Machines for the IDENTITY- and NOT Operators. IEEE Transactions on Pattern Analysis and Machine Intelligence. ISSN: 0162-8828. doi:10.1109/TPAMI.2021.3085591.
  • Yadav, Rohan Kumar; Lei, Jiao; Goodwin, Morten; Granmo, Ole-Christoffer (2021). Positionless aspect based sentiment analysis using attention mechanism.. Knowledge-Based Systems. ISSN: 0950-7051. 226doi:10.1016/j.knosys.2021.107136.
  • Abeyrathna, Kuruge Darshana; Rasca, Sinziana Ioana; Markvica, Karin; Granmo, Ole-Christoffer (2021). Public Transport Passenger Count Forecasting in Pandemic Scenarios Using Regression Tsetlin Machine. Case Study of Agder, Norway. Smart Innovation, Systems and Technologies. ISSN: 2190-3018. 231s 27 - 37. doi:10.1007/978-981-16-2324-0_4.
  • Abeyrathna, Darshana; Granmo, Ole-Christoffer; Shafik, Rishad; Yakovlev, Alex; Wheeldon, Adrian; Lei, Jie; Goodwin, Morten (2020). A Novel Multi-step Finite-State Automaton for Arbitrarily Deterministic Tsetlin Machine Learning. SGAI 2020: Artificial Intelligence XXXVII. ISBN: 9783030637989. Springer. Konferanseartikkel. s 108 - 122.
  • Abeyrathna, Kuruge Darshana; Granmo, Ole-Christoffer; Zhang, Xuan; Goodwin, Morten (2020). Adaptive Continuous Feature Binarization for Tsetlin Machines Applied to Forecasting Dengue Incidences in the Philippines. 2020 IEEE Symposium Series on Computational Intelligence (SSCI). ISBN: 978-1-7281-2547-3. IEEE. chapter. s 2084 - 2092.
  • Lazreg, Mehdi Ben; Goodwin, Morten; Granmo, Ole-Christoffer (2019). Combining a context aware neural network with a denoising autoencoder for measuring string similarities. Computer Speech and Language. ISSN: 0885-2308. 60doi:10.1016/j.csl.2019.101028.
  • Sharma, Jivitesh; Andersen, Per-Arne; Granmo, Ole-Christoffer; Goodwin, Morten (2020). Deep Q-Learning With Q-Matrix Transfer Learning for Novel Fire Evacuation Environment. IEEE Transactions on Systems, Man & Cybernetics. Systems. ISSN: 2168-2216. doi:10.1109/TSMC.2020.2967936.
  • Sharma, Jivitesh; Granmo, Ole-Christoffer; Goodwin, Morten (2020). Emergency Detection with Environment Sound Using Deep Convolutional Neural Networks. Proceedings of Fifth International Congress on Information and Communication Technology. ISBN: 978-981-15-5858-0. Springer Nature. 14. s 144 - 154.
  • Sharma, Jivitesh; Granmo, Ole-Christoffer; Goodwin, Morten (2020). Environment Sound Classification using Multiple Feature Channels and Attention based Deep Convolutional Neural Network. Interspeech (USB). ISSN: 2308-457X. s 1186 - 1190. doi:10.21437/Interspeech.2020-1303.
  • Andersen, Per-Arne; Goodwin, Morten; Granmo, Ole-Christoffer (2020). Increasing sample efficiency in deep reinforcement learning using generative environment modelling. Expert systems. ISSN: 0266-4720. doi:10.1111/exsy.12537.
  • Gorji, Saeed Rahimi; Granmo, Ole-Christoffer; Glimsdal, Sondre; Edwards, Jonathan; Goodwin, Morten (2020). Increasing the Inference and Learning Speed of Tsetlin Machines with Clause Indexing. Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices.. ISBN: 978-3-030-55789-8. Springer Nature. paper. s 695 - 708.
  • Yadav, Rohan Kumar; Bhattarai, Bimal; Lei, Jiao; Goodwin, Morten; Granmo, Ole-Christoffer (2020). Indoor Space Classification Using Cascaded LSTM. IEEE Conference on Industrial Electronics and Applications. ISSN: 2158-2297. s 1110 - 1114. doi:10.1109/ICIEA48937.2020.9248347.
  • Abeyrathna, Kuruge Darshana; Granmo, Ole-Christoffer; Goodwin, Morten (2020). Integer Weighted Regression Tsetlin Machines. Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices.. ISBN: 978-3-030-55789-8. Springer Nature. chapter. s 686 - 694.
  • Abeyrathna, Kuruge Darshana; Gardiyawasam Pussewalage, Harsha; Ranasinghe, Sasanka Niromi; Oleshchuk, Vladimir; Granmo, Ole-Christoffer (2020). Intrusion Detection with Interpretable Rules Generated Using the Tsetlin Machine. 2020 IEEE Symposium Series on Computational Intelligence (SSCI). ISBN: 978-1-7281-2547-3. IEEE. chapter. s 1121 - 1130.
  • Wheeldon, Adrian; Shafik, Rishad; Rahman, Tousif; Lei, Jie; Yakovlev, Alex; Granmo, Ole-Christoffer (2020). Learning automata based energy-efficient AI hardware design for IoT applications: Learning Automata based AI Hardware. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. ISSN: 1364-503X. 378 (2182). s 1 - 18. doi:10.1098/rsta.2019.0593.
  • Saha, Rupsa; Granmo, Ole-Christoffer; Goodwin, Morten (2020). Mining Interpretable Rules for Sentiment and Semantic Relation Analysis Using Tsetlin Machines. SGAI 2020: Artificial Intelligence XXXVII. ISBN: 9783030637989. Springer.
  • Abeyrathna, Kuruge Darshana; Granmo, Ole-Christoffer; Goodwin, Morten (2020). On Obtaining Classification Confidence, Ranked Predictions and AUC with Tsetlin Machines. 2020 IEEE Symposium Series on Computational Intelligence (SSCI). ISBN: 978-1-7281-2547-3. IEEE. chapter. s 662 - 669.
  • Andersen, Per-Arne; Goodwin, Morten; Granmo, Ole-Christoffer (2020). Safer Reinforcement Learning for Agents in Industrial Grid-Warehousing. Machine Learning, Optimization, and Data Science: 6th International Conference, LOD 2020. ISBN: 978-3-030-64579-3. Springer Nature. chapter. s 169 - 180.
  • Andersen, Per-Arne; Goodwin, Morten; Granmo, Ole-Christoffer (2020). Towards safe reinforcement-learning in industrial grid-warehousing. Information Sciences. ISSN: 0020-0255. 537s 467 - 484. doi:10.1016/j.ins.2020.06.010.
  • 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.
  • Lazreg, Mehdi Ben; Goodwin, Morten; Granmo, Ole-Christoffer (2019). A Neural Turing~Machine for Conditional Transition Graph Modeling. arXiv.org. ISSN: 2331-8422.
  • 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. paper. s 564 - 578.
  • Gorji, Saeed Rahimi; Granmo, Ole-Christoffer; Phoulady, Adrian; Goodwin, Morten (2019). A Tsetlin Machine with Multigranular Clauses. Lecture Notes in Computer Science (LNCS). ISSN: 0302-9743. doi:10.1007/978-3-030-34885-4_11.
  • Lazreg, Mehdi Ben; Goodwin, Morten; Granmo, Ole-Christoffer (2019). An Iterative Information Retrieval Approach from Social Media in Crisis Situations. 2019 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM). ISBN: 978-1-7281-4920-2. IEEE conference proceedings. chapter.
  • Abouzeid, Ahmed Abdulrahem Othman; Granmo, Ole-Christoffer; Webersik, Christian; Goodwin, Morten (2019). Causality-based Social Media Analysis for Normal Users Credibility Assessment in a Political Crisis. Proceedings of the [xx]th Conference of Open Innovations Association FRUCT. ISSN: 2305-7254. doi:10.23919/FRUCT48121.2019.8981500.
  • Sharma, Jivitesh; Andersen, Per-Arne; Granmo, Ole-Christoffer; Goodwin, Morten (2019). Deep Q-Learning with Q-Matrix Transfer Learning for Novel Fire Evacuation Environment. arXiv.org. ISSN: 2331-8422. doi:10.1109/tsmc.2020.2967936.
  • Sharma, Jivitesh; Granmo, Ole-Christoffer; Goodwin, Morten (2019). Environment Sound Classification using Multiple Feature Channels and Deep Convolutional Neural Networks. arXiv.org. ISSN: 2331-8422.
  • Sharma, Jivitesh; Matheussen, Bernt Viggo; Glimsdal, Sondre; Granmo, Ole-Christoffer (2019). Hydropower Optimization Using Split-Window, Meta-Heuristic and Genetic Algorithms. 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA). ISBN: 978-1-7281-4550-1. IEEE conference proceedings. chapter.
  • Matheussen, Bernt Viggo; Granmo, Ole-Christoffer; Sharma, Jivitesh (2019). Hydropower optimization using deep learning. Lecture Notes in Computer Science (LNCS). ISSN: 0302-9743. 11606 LNAIs 110 - 122. doi:10.1007/978-3-030-22999-3_11.
  • Sharma, Jivitesh; Giri, Charul; Granmo, Ole-Christoffer; Goodwin, Morten (2019). Multi-layer intrusion detection system with ExtraTrees feature selection, extreme learning machine ensemble, and softmax aggregation. EURASIP Journal on Information Security. ISSN: 2510-523X. 2019 (1). doi:10.1186/s13635-019-0098-y.
  • Havelock, Jessica; Oommen, John; Granmo, Ole-Christoffer (2019). On Using “Stochastic Learning on the Line” to Design Novel Distance Estimation Methods for Three-Dimensional Environments. Advances and Trends in Artificial Intelligence. From Theory to Practice. IEA/AIE 2019. ISBN: 978-3-030-22998-6. Springer. chapter. s 39 - 49.
  • Granmo, Ole-Christoffer; Glimsdal, Sondre; Lei, Jiao; Goodwin, Morten; Omlin, Christian; Berge, Geir Thore (2019). The Convolutional Tsetlin Machine. arXiv.org. ISSN: 2331-8422.
  • 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. s 268 - 280.
  • Abeyrathna, Kuruge Darshana; Granmo, Ole-Christoffer; Zhang, Xuan; Lei, Jiao; Goodwin, Morten (2019). The regression Tsetlin machine: a novel approach to interpretable nonlinear regression. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. ISSN: 1364-503X. doi:10.1098/rsta.2019.0165.
  • 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 (LNCS). ISSN: 0302-9743. 11606 LNAIs 71 - 78. doi:10.1007/978-3-030-22999-3_7.
  • Glimsdal, Sondre; Granmo, Ole-Christoffer (2019). Thompson sampling guided stochastic searching on the line for deceptive environments with applications to root-finding problems. Journal of machine learning research. ISSN: 1532-4435. 20doi:10.1109/icmla.2015.203.
  • Andersen, Per-Arne; Goodwin, Morten; Granmo, Ole-Christoffer (2019). Towards Model-Based Reinforcement Learning for Industry-Near Environments. Lecture Notes in Computer Science (LNCS). ISSN: 0302-9743. 11927 LNAIs 36 - 49. doi:10.1007/978-3-030-34885-4_3.
  • Andersen, Per-Arne; Goodwin, Morten; Granmo, Ole-Christoffer (2019). Towards Model-based Reinforcement Learning for Industry-near Environments. arXiv.org. ISSN: 2331-8422. doi:10.1007/978-3-030-34885-4_3.
  • Berge, Geir Thore; Granmo, Ole-Christoffer; Tveit, Tor Oddbjørn; Goodwin, Morten; Lei, Jiao; Matheussen, Bernt Viggo (2019). Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization With Medical Applications. IEEE Access. ISSN: 2169-3536. 7doi:10.1109/ACCESS.2019.2935416.
  • 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 (LNCS). 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. NIKT: Norsk IKT-konferanse for forskning og utdanning. 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 (LNCS). 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 (LNCS). 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. NIKT: Norsk IKT-konferanse for forskning og utdanning. 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 (LNCS). 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 (LNCS). 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 (IJISCRAM). 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 (LNCS). 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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 Sarnoff Symposium. 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.
  • 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 (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. 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.
  • 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.
  • Følstad, Asbjørn; Araujo, Theo; Papadopoulos, Symeon; Law, Effie L.-C.; Granmo, Ole-Christoffer; Luger, Ewa; Brandtzæg, Petter Bae (2020). Chatbot Research and Design. Third International Workshop, CONVERSATIONS 2019, Amsterdam, The Netherlands, November 19–20, 2019, Revised Selected Papers.. ISBN: 978-3-030-39540-7. Springer. s 273.
  • Yadav, Rohan Kumar; Lei, Jiao; Granmo, Ole-Christoffer; Goodwin, Morten (2021). Interpretability in Word Sense Disambiguation using Tsetlin Machine.

Last changed: 14.01.2019 23:01