Dr. scient. Ole-Christoffer Granmo

Name: Ole-Christoffer Granmo Position: Professor; Coordinator - International Master's Programme in ICT Institution: Department of ICT, University of Agder Office: A3 062, Campus Grimstad E-mail: ole.granmo@uia.no Phone: +47 37 23 33 57 Fax: +47 38 14 10 01

Teaching

• Learning Systems

Research Interests

• Intelligent Systems
• Stochastic Modelling and Inference
• Machine Learning
• Pattern Recognition
• Learning Automata
• Distributed Computing
• Surveillance and Monitoring

Projects

• SmartRescue - Smartphones for Coordinated Threat Assessment and Evacuation Planning. Jan 2012 to Jan 2015. An overview of the SmartRescue project can be found in the Fourth ISCRAM Newsletter, December 2011.

PhD Students

• Sondre Glimsdal. Title TBD. August 2011 to Date.
• Xuan Zhang. Learning Automata – Bayesian Estimator Algorithms. May 2010 to Date.
• Anis Yazidi. Intelligent Learning Automata-based Strategies Applied to Personalized Service Provisioning in Pervasive Environments. University of Agder and Ericsson Research. Nov 2008 to Date.

Journal Papers

1. Anis Yazidi, Ole-Christoffer Granmo and B. John Oommen. On the Analysis of a Random Interleaving Walk-Jump Process with Applications to Testing. To Appear in Sequential Analysis. (Accepted August 27, 2011)
2. Anis Yazidi, Ole-Christoffer Granmo, B. John Oommen, Martin Gerdes and Frank Reichert. A User-Centric Approach for Personalized Service Provisioning in Pervasive Environments. To Appear in Wireless Personal Communication. (Accepted June 21, 2011)
3. Noureddine Bouhmala and Ole-Christoffer Granmo. GSAT Enhanced with Learning Automata and Multilevel Paradigm. To Appear in International Journal of Computer Science Issues. (Accepted May 31, 2011)
4. Anis Yazidi, Ole-Christoffer Granmo and B. John Oommen. Service Selection in Stochastic Environments: A Learning-Automaton Based Solution. To Appear in Applied Intelligence. (Accepted January 17, 2011)
5. Ole-Christoffer Granmo and B. John Oommen. Learning Automata-based Solutions to the Optimal Web Polling Problem Modelled as a Nonlinear Fractional Knapsack Problem. In Engineering Applications of Artificial Intelligence, Volume 24, Issue 7, October 2011, pp. 1238-1251.
6. Noureddine Bouhmala and Ole-Christoffer Granmo. Stochastic Learning for SAT-Encoded Graph Coloring Problems. In International Journal of Applied Metaheuristic Computing, Volume 1, Issue 3, July-September 2010, pp. 1-19.
7. Ole-Christoffer Granmo and B. John Oommen. Optimal sampling for estimation with constrained resources using a learning automaton-based solution for the nonlinear fractional knapsack problem. In Applied Intelligence, Volume 33, Number 1, August 2010, pp. 3-20.
8. Noureddine Bouhmala and Ole-Christoffer Granmo. Combining Finite Learning Automata with GSAT for the Satisfiability Problem. In Engineering Applications of Artificial Intelligence (EAAI), Volume 23, Issue 5, August 2010, pp. 715-726.
9. Ole-Christoffer Granmo and B. John Oommen. Solving Stochastic Nonlinear Resource Allocation Problems Using a Hierarchy of Twofold Resource Allocation Automata. In IEEE Transactions on Computers, Volume 59, Issue 4, April 2010, pp. 545-560.
10. Ole-Christoffer Granmo. Solving Two-Armed Bernoulli Bandit Problems Using a Bayesian Learning Automaton. In International Journal of Intelligent Computing and Cybernetics (IJICC), Volume 3, Issue 2, 2010, pp. 207 - 234.
11. B. John Oommen, Sang-Woon Kim, T. Mathew and Ole-Christoffer Granmo. A Solution to the Stochastic Point Location Problem in Metalevel Nonstationary Environments. In IEEE Transactions on Systems, Man and Cybernetics, Part B, Volume 38, Issue 2, April 2008, pp. 466-476.
12. Ole-Christoffer Granmo and Noureddine Bouhmala. Solving the Satisfiability Problem Using Finite Learning Automata. In International Journal of Computer Science and Applications, Volume 4, Issue 3, December 2007, pp. 15-29.
13. Ole-Christoffer Granmo and Vladimir A. Oleshchuk. Privacy Preserving Data Mining in Telecommunication Services. In Telektronikk, Volume 103, Issue 2, August 2007, pp. 84-89.
14. B. John Oommen, Sudip Misra and Ole-Christoffer Granmo. Routing Bandwidth Guaranteed Paths in MPLS Traffic Engineering: A Multiple Race Track Learning Approach. In IEEE Transactions on Computers, Volume 56, Issue 7, July 2007, pp. 959-976.
15. Ole-Christoffer Granmo, B. John Oommen, Svein-Arild Myrer and Morten G. Olsen. Learning Automata-based Solutions to the Nonlinear Fractional Knapsack Problem with Applications to Optimal Resource Allocation. In IEEE Transactions on Systems, Man and Cybernetics, Part B, Volume 37, Issue 1, February 2007, pp. 166-175.
16. Viktor S. Wold Eide, Ole-Christoffer Granmo, Frank Eliassen and Jørgen Andreas Michaelsen. Real-time Video Content Analysis: QoS-Aware Application Composition and Parallel Processing. In ACM Transactions on Multimedia Computing, Communications, and Applications (ACM TOMCCAP), Volume 2, Issue 2, May 2006, pp. 149-172.
17. Ole-Christoffer Granmo. Pipelined Execution of a Parallel Particle Filter for Real-time Feature Selection and Classification in Data Streams. In WSEAS Transactions on Information Science and Applications, Volume 1, Issue 3, September 2004, pp. 872-879.

Conference Papers

1. Anis Yazidi, Ole-Christoffer Granmo and B. John Oommen. Tracking the Preferences of Users Using Weak Estimators. To Appear in Proceedings of the 2011 Australasian Joint Conference on Artificial Intelligence (AI'11), Perth, Australia, December 2011.
2. Xuan Zhang, B. John Oommen and Ole-Christoffer Granmo. Generalized Bayesian Pursuit: A Novel Scheme for Multi-Armed Bernoulli Bandit Problems. In Proceedings of the 2011 Conference on Artificial Intelligence Applications and Innovations (AIAI'11), IFIP Advances in Information and Communication Technology, pp. 122-131, Springer, Corfu, Greece, September 2011.
3. Vegard Haugland, Marius Kjølleberg, Svein-Erik Larsen and Ole-Christoffer Granmo. A Two-Armed Bandit Collective for Examplar Based Mining of Frequent Itemsets with Applications to Intrusion Detection. In Proceedings of 3rd International Conference on Computational Collective Intelligence - Technologies and Applications (ICCCI 2011), Lecture Notes in Computer Science 6922, pp. 72-81, Springer, Gdynia, Poland, September 2011.
4. Ole-Christoffer Granmo and Sondre Glimsdal. A Two-Armed Bandit Based Scheme for Accelerated Decentralized Learning. In Proceedings of the 2011 International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA-AIE 2011), Lecture Notes in Computer Science 6704, pp. 532-541, Springer, Syracuse, USA, June/July 2011.
5. Xuan Zhang, Ole-Christoffer Granmo and B. John Oommen. The Bayesian Pursuit Algorithm: A New Family of Estimator Learning Automata. In Proceedings of the 2011 International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA-AIE 2011), Lecture Notes in Computer Science 6704, pp. 522-531, Springer, Syracuse, USA, June/July 2011.
6. Anis Yazidi, Ole-Christoffer Granmo, B. John Oommen, Frank Reichert and Martin Gerdes. An Intelligent Architecture for Service Provisioning in Pervasive Environments. In Proceedings of the 2011 International Symposium on Innovations in Intelligent Systems and Applications (ISIISA'11), pp. 524-530, IEEE, Istanbul, Turkey, June 2011.
7. Anis Yazidi, Ole-Christoffer Granmo and B. John Oommen. A New Tool for the Modeling of AI and Machine Learning Applications: Random Walk-Jump Processes. In Proceedings of the 2011 International Conference on Hybrid Artificial Intelligence Systems (HAIS'11), Wroclaw, Poland, May 2011, pp. 11-21. This talk was a Plenary/Keynote Talk at the Conference.
8. Anis Yazidi, Ole-Christoffer Granmo and B. John Oommen. On the Analysis of a New Markov Chain Which has Applications in AI and Machine Learning. In Proceedings of the 2011 Annual Canadian Conference on Electrical and Computer Engineering (CCECE'11), IEEE, Niagara Falls, Canada, May 2011.
9. Anis Yazidi, Ole-Christoffer Granmo, Min Lin, Xifeng Wen, B. John Oommen, Martin Gerdes and Frank Reichert. Learning Automaton Based On-line Discovery and Tracking of Spatio-Temporal Event Patterns. In Proceedings of the 2010 Pacific Rim International Conference on Artificial Intelligence, Lecture Notes in Artificial Intelligence 6230, pp. 327-338, Springer, Daegu, Korea, August/September 2010.
10. Aleksander Stensby, B. John Oommen and Ole-Christoffer Granmo. Language Detection and Tracking in Multilingual Documents Using Weak Estimators. In Proceedings the 2010 International Symposium on Structural, Syntactic and Statistical Pattern Recognition, Lecture Notes in Computer Science 6218, pp. 600-609, Springer, Izmir, Turkey, August 2010.
11. Anis Yazidi, Ole-Christoffer Granmo and B. John Oommen. A Learning Automata Based Solution to Service Selection in Stochastic Environments. In Proceedings of the Twenty Second International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems (IEA-AIE 2010), Lecture Notes in Artificial Intelligence 6098, pp. 209-218, Springer, Cordoba, Spain, June 2010.
12. Ole-Christoffer Granmo and Stian Berg. Solving Non-Stationary Bandit Problems by Random Sampling from Sibling Kalman Filters. In Proceedings of the Twenty Third International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems (IEA-AIE 2010), Lecture Notes in Artificial Intelligence 6098, Springer, Cordoba, Spain, June 2010.
13. Ole-Christoffer Granmo and Noureddine Bouhmala. Enhancing Local-Search Based SAT Solvers with Learning Capability. In Proceedings of the Second International Conference on Agents and Artificial Intelligence (ICAART 2010), pp. 515-521, Valencia, Spain, January 2010.
14. Thomas Norheim, Terje Brådland, Ole-Christoffer Granmo and B. John Oommen. A Generic Solution to Multi-Armed Bernoulli Bandit Problems Based on Random Sampling from Sibling Conjugate Priors. In Proceedings of the Second International Conference on Agents and Artificial Intelligence (ICAART 2010), pp. 36-44, Valencia, Spain, January 2010.
15. Ole-Christoffer Granmo and B. John Oommen. A Hierarchy of Twofold Resource Allocation Automata Supporting Optimal Sampling. In Proceedings of the Twenty Second International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems (IEA-AIE 2009), Lecture Notes in Computer Science 5579, pp. 523-534, Springer, Taiwan, June 2009. This paper won the Best Paper Award of the Conference.
16. B. John Oommen, Ole-Christoffer Granmo and Zuoyuan Liang. A Novel Stochastic Learning-Enhanced Multidimensional Scaling Technique Applicable for Word-Of-Mouth Discussions. In Proceedings of the Twenty Second International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems (IEA-AIE 2009) , Studies in Computational Intelligence 214, pp. 317-322, Springer, Taiwan, June 2009.
17. Ole-Christoffer Granmo. A Bayesian Learning Automaton for Solving Two- Armed Bernoulli Bandit Problems. In Proceedings of The Seventh International Conference on Machine Learning and Applications (ICMLA'08), pp. 23-30, IEEE, San Diego, December 2008.
18. Ole-Christoffer Granmo. The Bayesian Learning Automaton . Empirical Evaluation with Two-Armed Bernoulli Bandit Problems. In Research and Development in Intelligent Systems XXV, pp. 235-248, Springer, 2008.
19. Ole-Christoffer Granmo and B. John Oommen. A Hierarchy of Twofold Resource Allocation Automata Supporting Optimal Web Polling. In Proceedings of the Twenty-First International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE-08), Lecture Notes in Artificial Intelligence 5027, pp. 347-358, Springer, Wroclaw, Poland, June 2008.
20. Noureddine Bouhmala and Ole-Christoffer Granmo. Solving Graph Coloring Problems Using Learning Automata. In Proceedings of the Eighth European Conference on Evolutionary Computation in Combinatoral Optimisation, Lecture Notes in Computer Science 4972, pp. 277-288, Springer, Napoli, Italy, March 2008.
21. Ole-Christoffer Granmo and B. John Oommen. On Using a Hierarchy of Twofold Resource Allocation Automata to Solve Stochastic Nonlinear Resource Allocation Problems. In Proceedings of the 2007 Australian Joint Conference on Artificial Intelligence (AI'07), Lecture Notes in Computer Science 4830, pp. 36-47, Springer, Gold Coast, Australia, December 2007.
22. B. John Oommen, Sang-Woon Kim, Mathew Samuel and Ole-Christoffer Granmo. Stochastic Point Location in Non-stationary Environments and Its Applications. In Proceedings of the Twentieth International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE 2007), Lecture Notes in Computer Science 4570, pp. 845-854, Springer, Kyoto, Japan, June 2007.
23. B. John Oommen, Ole-Christoffer Granmo and Asle Pedersen. Using Stochastic AI Techniques to Achieve Unbounded Resolution in Finite Player Goore Games and its Applications. In Proceedings of the 2007 IEEE Symposium on Computational Intelligence and Games, pp. 161-167, Honolulu, Hawaii, April 2007.
24. B. John Oommen, Ole-Christoffer Granmo and Asle Pedersen. Empirical Verification of a Strategy for Unbounded Resolution in Finite Player Goore Games. In Proceedings of the 19th Australian Joint Conference on Artificial Intelligence (AI 2006), Lecture Notes in Artificial Intelligence 4304, pp. 1252-1258, Springer, Hobart, Tasmania, December 2006.
25. Ole-Christoffer Granmo and B. John Oommen. On Allocating Limited Sampling Resources Using a Learning Automata-based Solution to the Fractional Knapsack Problem. In Proceedings of the 2006 International Intelligent Information Processing and Web Mining Conference (IIS:IIPW'06), Advances in Soft Computing, Volume 35, pp. 263-272, Springer, Ustron, Poland, June 2006.
26. Ole-Christoffer Granmo, B. John Oommen, Svein-Arild Myrer and Morten G. Olsen. Determining Optimal Polling Frequency Using a Learning Automata-based Solution to the Fractional Knapsack Problem. In Proceedings of the 2006 IEEE International Conferences on Cybernetics & Intelligent Systems (CIS) and Robotics, Automation & Mechatronics (RAM), Bangkok, Thailand, June 2006.
27. B. John Oommen, Sudip Misra and Ole-Christoffer Granmo. Stochastic Random-Races Algorithm for Routing in MPLS Traffic Engineering. In Proceedings of the 2006 IEEE Annual Conference on Computer Communications (IEEE INFOCOM 2006), Barcelona, Spain, April 2006.
28. Ole-Christoffer Granmo. Pipelined Execution of a Parallel Particle Filter for Real-time Feature Selection and Classification in Data Streams. In Proceedings of the 4th WSEAS International Conference on Signal, Speech and Image Processing (ICOSSIP 2004), Izmir, Turkey, September 2004. (pdf)
29. Ole-Christoffer Granmo. Parallel Hypothesis Driven Video Content Analysis. In Proceedings of the 2004 ACM Symposium on Applied Computing (SAC 2004), pp. 642-648, ACM Press, Nicosia, Cyprus, March 2004. (pdf)
30. Viktor S. Wold Eide, Frank Eliassen, Ole-Christoffer Granmo and Olav Lysne. Supporting Timeliness and Accuracy in Distributed Real-time Content-based Video Analysis. In Proceedings of the 2003 Annual ACM International Conference on Multimedia (MM'03), pp. 21-32, ACM Press, Berkeley, California, USA, November 2003. (pdf)
31. Ole-Christoffer Granmo, Frank Eliassen, Olav Lysne and Viktor S. Wold Eide. Techniques for Parallel Execution of the Particle Filter. In Proceedings of the 13th Scandinavian Conference on Image Analysis (SCIA2003), Lecture Notes in Computer Science 2749, pp. 983-990, Springer, Gøteborg, Sweden, June/July 2003. (pdf)
32. Ole-Christoffer Granmo, Vladimir Oleshchuk and Mikael Snaprud. Towards a Probabilistic Framework for Analogous Multi-Modal Human-Computer Interaction. In Proceedings of the 10th International Conference on Human - Computer Interaction (HCII2003), vol. 4, pp. 1407-1411, Lawrence Erlbaum Associates, Inc., Crete, Greece, June 2003.
33. Mikael Snaprud, Nils Ulltveit-Moe, Ole-Christoffer Granmo, Michael Rafoshei-Klev, Arne Wiklund and Agata Sawicka. Quantitative Assessment of Public Web Sites Accessibility - Some Early Results. In Proceedings of the Accessibility for All Conference 2003, Nice, France, March 2003.
34. Viktor S. Wold Eide, Frank Eliassen, Ole-Christoffer Granmo and Olav Lysne. Scalable Independent Multi-level Distribution in Multimedia Content Analysis. In Protocols and Systems for Interactive Distributed Multimedia (IDMS/PROMS 2002), Lecture Notes in Computer Science 2515, pp. 37-48, Springer, Coimbra, Portugal, November 2002. (pdf)
35. Viktor S. Wold Eide, Frank Eliassen, Olav Lysne and Ole-Christoffer Granmo. Real-time Processing of Media Streams: A Case for Event-based Interaction. In Proceedings of the International Workshop on Distributed Event-Based Systems (DEBS'02), pp. 555-562, Vienna, Austria, July 2002. (pdf)
36. Ole-Christoffer Granmo and Finn Verner Jensen. Real-time Hypothesis Driven Feature Extraction on Parallel Processing Architectures. In Proceedings of the 2002 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA'02), vol. 2, pp. 727-733, Las Vegas, USA, June 2002. (pdf)
37. Ole-Christoffer Granmo. Automatic Resource-aware Construction of Media Indexing Applications for Distributed Processing Environments. In Proceedings of the 2nd International Workshop on Pattern Recognition in Information Systems (PRIS2002), pp. 124-139, Alicante, Spain, April 2002. (pdf)
38. Ole-Christoffer Granmo, Frank Eliassen and Olav Lysne. Dynamic object-oriented Bayesian networks for flexible resource-aware content-based indexing of media streams. In Proceedings of the 12th Scandinavian Conference on Image Analysis (SCIA2001), pp. 587-594, Bergen, Norway, June 2001. (pdf)
39. Viktor S. Wold Eide, Frank Eliassen, Ole-Christoffer Granmo and Olav Lysne. Distributed Journaling of Distributed Media. In Proceedings of the Norwegian Computer Science Conference (NIK'2000), Bodø, Norway, November 2000. (pdf)

Book Chapters

1. Ole-Christoffer Granmo and Noureddine Bouhmala. Using Learning Automata to Enhance Local-Search Based SAT Solvers with Learning Capability. In Application of Machine Learning, pp. 63-85. Published by In-Teh. Edited by Yagang Zhang, 2010. (pdf)
2. Ole-Christoffer Granmo and B. John Oommen. Learning Automata-based Solutions to Stochastic Nonlinear Resource Allocation Problems. In Intelligent Systems for Knowledge Management, SCI 252, pp. 1-30. Published by Springer Publishers. Edited by N. T. Nguyen and E. Szczerbicki, 2010.
3. B. John Oommen and Ole-Christoffer Granmo. Learning Automata-based Solutions to the Goore Game and its Applications. In Game Theory: Strategies, Equilibria, and Theorems. Published by Nova Science Publishers, New York. Edited by F. Columbus, 2008.

Technical Reports

• Viktor S. Wold Eide, Frank Eliassen, Olav Lysne and Ole-Christoffer Granmo. Extending Content-based Publish/Subscribe Systems with Multicast Support, Simula Research Laboratory, Technical Report 2003-03, July 2003. (pdf)

Master Theses Supervised

1. Jan Gunnar Andreassen and Lars Magne Engedal. Model Calibration with Hierarchically Structured Bayesian Learning Automata. Master Thesis, University of Agder, June 2011.
2. Vegard Haugland, Marius Kjølleberg and Svein-Erik Larsen. Anomaly Detection in Computer Networks Using Hierarchically Organized Teams of Learning Automata. Master Thesis, University of Agder, June 2011. Received Best Master Thesis in ICT of the Year Award at Faculty of Engineering and Science, University of Agder.
3. Vimala Nunavath and Mohammad Yasar. Pattern Recognition Based Prediction of the Outcome of Radiotherapy in Cervical Cancer Treatment. Master Thesis, University of Agder, June 2011.
4. Felipe Dalevoll Macedo. Probabilistic Decoding of Sentiment. Master Thesis, University of Agder, June 2011.
5. Tarjei Romtveit. Load-balancing by Applying a Bayesian Learning Automata (BLA) Scheme in a Non-Stationary Web-Crawler Network. Master Thesis, University of Agder, June 2010. Received Best Master Thesis in ICT of the Year Award at Faculty of Engineering and Science, University of Agder. (pdf)
6. Stian Berg. Solving Dynamic Bandit Problems and Decentralized Games using the Kalman Bayesian Learning Automaton. Master Thesis, University of Agder, June 2010. (pdf)
7. Nadja Vidnes. Gradient Descent Algorithm Incorporating Stochastic Point Location Schemes and Its Application in Multidimensional Scaling Analysis. Master Thesis, University of Agder, June 2010. (pdf)
8. Thomas Hansen Gøytil and Andreas Lundberg. A novel spatio-temporal scheme for reducing the rate of false positives in Bloom Filter based URL-caching. Master Thesis, University of Agder, June 2010. (pdf)
9. Magnus Bjerkeseth. Using Hidden Markov Models for fault diagnostics and prognostics in Condition Based Maintenance systems. Master Thesis, University of Agder, June 2010. (pdf)
10. Yokun Gao and Karl Kristian Grythe. Uncertainty Analysis of Hydrometeorological Forecasts. Master Thesis, University of Agder, June 2010. (pdf)
11. Tom Sverre Hageland and Roger Tjosås. Automatic Calibration of Numerical Model Using Artificial Intelligence Based Techniques. Master Thesis, University of Agder, June 2010. (pdf)
12. Jan Olsen. Recommending Services in Pervasive Environments. Master Thesis, University of Agder, June 2010. (pdf)
13. Terje Brådland and Thomas Norheim. Empirical Evaluation of the Bayesian Learning Automaton Family. Master Thesis, University of Agder, June 2009. Received Best Master Thesis in ICT of the Year Award at Faculty of Engineering and Science, University of Agder. (pdf)
14. Torbjørn Skagestad, Kristian Tveiten and Christian Auby. Detecting Malicious Network Activity Using Flowdata and Learning Automata. Master Thesis, University of Agder, June 2009. (pdf)
15. Frode Nilsen. Problem/Issue Detection and Classification. Master Thesis, University of Agder, June 2009. (pdf)
16. Erik Victor Hvistendahl and Xiongjie Chen. Automatic Data Extraction from Online Discussion Boards. Master Thesis, University of Agder, June 2009. (pdf)
17. Gjermund Karlsen Lie. Playing Axis and Allies Revised Using Learning Automata. Master Thesis, University of Agder, June 2009. (pdf)
18. Min Lin and Xifeng Wen. Handling Relations in a Ubiquitous Compuitng Environment. Master Thesis, University of Agder, June 2009. (pdf)
19. Terje Leira and Anis Yazidi. Process Improvement Solution for Mobile Platform Customer SW Development. Master Thesis, University of Agder, June 2008.
20. Aleksander Møller Stensby. Stochastic Learning-Based Estimation Methods for Pattern Recognition and Its Application to Topic Detection and Tracking. Master Thesis, University of Agder, June 2008. Received Best Master Thesis in ICT of the Year Award at Faculty of Engineering and Science, University of Agder.
21. Wenjie Li. Finding Optimal Rush Attacks in Real Time Strategy (RTS) Games. Master Thesis, University of Agder, June 2008.
22. Walid Trabelsi. Software Development Process Improvement in Datacom Platform. Master Thesis, University of Agder, June 2008.
23. Roberth Vestbø. Battery Preserving Activation of Sensors in Wireless Sensor Networks. Master Thesis, Agder University College, June 2007. (pdf)
24. Jaran Nilsen. Locating Discussion Board Users with Bayesian Analysis of Geographic Terms, Language and Timestamps. Master Thesis, Agder University College, June 2007. (pdf)
25. Morten S. Staalesen and Thomas Torland. Intelligent Systems: Identifying and Exploiting the Weakest Point in a Defense. Master Thesis, Agder University College, June 2007. (pdf)
26. Olav Jensen, Kjetil Monge and Raymond Koteng. Enhancing Hierarchical Clustering with Local Search. Master Thesis, Agder University College, June 2007. (pdf)
27. Arild Finne and Erik Tradal. Data Management and Concurrency Control in Broadcast based Asymmetric Environments. Master Thesis, Agder University College, June 2006. (pdf)
28. Jørgen Andersen and Jan Roar Edvardsen. Test-Driven Development of Ajax Enabled Web Applications on the Java Platform. Master Thesis, Agder University College, June 2006. (pdf)
29. Svein Arild Myrer and Morten Goodwin Olsen. Incremental Web Crawling as a Competitive Game of Learning Automata. Master Thesis, Agder University College, June 2005. Received Best Master Thesis in ICT of the Year Award at Faculty of Engineering and Science, Agder University College.(pdf)
30. Andre Andersen, Jørgen de Lange and Tomas Skøie. A Scalable and QoS-aware Architecture for Content-based Distribution of Voluminous Data across WANs. Master Thesis, Agder University College, June 2005. (pdf)
31. Tor Oskar Wilhelmsen. Self-organized Learning of Traffic Categories in Bayesian Packet Based Intrusion Detection. Master Thesis, Agder University College, June 2005. (pdf)
32. Roar Hauger and Nils-Edvard Lileng Holene. Automatic Analysis of Oil Well Lithology based on the Naive Bayesian Classifier and the Hidden Markov Model. Master Thesis, Agder University College, June 2005. (pdf)
33. Henning Hetland and Tor-Øyvind Eriksen. Interconnected Learning Automata Playing Iterated Prisoner's Dilemma. Master Thesis, Agder University College, June 2004. Received Best Master Thesis in ICT of the Year Award at Faculty of Engineering and Science, Agder University College.(pdf)
34. Håvard Bakke and Torbjørn Meland. Middleware for Transparent TCP Connection Migration. Master Thesis, Agder University College, June 2004. (doc)
35. John Bildøy, Stian Clausen and Tor-Erik Klausen. Classifying Alerts in Multi-tier Intrusion Detection Systems. Master Thesis, Agder University College, June 2004. (pdf)