Publications

(DEST Cat.)

Books

  1. Korb, K., & Nicholson, A. (2011). Bayesian Artificial Intelligence. 2nd Edition,Boca Raton, FL, USA: CRC Press. (A4)
  2. Mascaro, S., Korb, K., Nicholson, A., & Woodberry, O. (2010). Evolving Ethics: The New Science of Good and Evil. Exeter, UK: Imprint Academic. (A1)
  3. A E Nicholson and X Li (eds) (2009).  Proceedings of the 22nd Australasian Joint Conference on Advances in Artificial Intelligence, Springer-Verlag, Berlin Germany. (A3)
  4. K.B. Korb and A.E. Nicholson (2004). Bayesian Artificial Intelligence. Chapman Hall/CRC Press, Boca Raton, Fl. (A1)

Book chapters

  1. Nicholson, A.E. and Korb, K.B. Bayesian networks for biosecurity. In Walshe, T., Burgman, M, Robinson, A (Eds.) Risk-based decisions for biological threats. Cambridge University Press. (B1)
  2. Wen, Y., Korb, K., & Nicholson, A. (2010). ‘Generating incomplete data with DataZapper’ In J. Filipe, A. Fred & B. Sharp (Eds.), Agents and Artificial Intelligence (pp. 110-123). Berlin, Germany: Springer-Verlag. (B1)
  3. A. E. Nicholson, C. R. Twardy, K. B. Korb, L. R. Hope (2008), “Decision support for clinical cardiovascular risk assessment”, in O. Pourret, P. Naim and B.G. Marcot, (Eds) Bayesian Belief Networks: A Practical Guide to Applications, Wiley. (B1)
  4. K.B. Korb and A. E. Nicholson (2008), “The causal interpretation of Bayesian networks”, in L. Jain and D.E. Holmes (Eds) Innovations in Bayesian Networks: Theory and Application, Springer-Verlag, Berlin Germany, pp. 83-116. (B1)

Refereed Journal Articles

  1. Wintle, B.C., & Nicholson, A.E. (2014). Exploring risk judgments in a trade dispute using Bayesian Networks. Risk Analysis. (C1)
  2. Mascaro, S., Korb, K.B., and Nicholson, A.E. Anomaly Detection in Vessel Tracks using Bayesian Networks. (2014). International Journal of Approximate Reasoning, vol 55, issue 1,  Elsevier Science, Amsterdam Netherlands, pp. 84-96. (C1)
  3. Sesen, M.B, Nicholson, A.E, Banares-Alcantara, R., Kadir, T. and Brady, M. (2013). Bayesian Networks for Clinical Decision Support in Lung Cancer Care. PLOS ONE.8(12), e82349 (C1)
  4. J. Baum, A E Nicholson and T I Dix (2013). Proximity-based Non-uniform Abstractions for Approximate Planning. Journal of Artificial Intelligence Research, vol 43, pp. 477-522. (C1)
  5. M J Flores, A E Nicholson, A Brunskill, K B Korb, S Mascaro (2011).  Incorporating expert knowledge when learning Bayesian network structure: A medical case study, Artificial Intelligence in Medicine, vol 53, issue 3, Elsevier Science, Amsterdam Netherlands, pp. 181-204. (C1)
  6. P Jimenez Andrioli, B Shirinzadeh, D Oetomo and A Nicholson: Swarm aggregation and formation control for robots with limited perception, International Journal of Robotics and Automation, vol 26, issue 3, ACTA Press, Calgary Canada, pp. 255-263. (C1)
  7. A E Nicholson and M J Flores (2011) Combining state and transition models with dynamic Bayesian networks, Ecological Modelling, vol 222, issue 3, Elsevier Science BV, Amsterdam Netherlands, pp. 555-566. (C1)
  8. O. Woodberry, K.B. Korb  and A.E. Nicholson (2007), A Simulation study of the Evolution of Aging,’ Evolutionary Ecology Research, 9(7), pp. 1077-1096. (C1)
  9. A. Tang, A. Nicholson, Y. Jin, J. Han (2007). Using Bayesian Belief Networks for Change Impact Analysis in Architecture Design. Journal of Systems and Software. vol 80, issue 1, Elsevier Inc, USA, pp. 127-148. (C1)
  10. C.A. Pollino, O. Woodberry, A.E. Nicholson, K.B. Korb, B. T. Hart  (2007). Parameterisation of a Bayesian network for use in an ecological risk management case study. Journal of Environmental Modelling and Software.  22(8), pp. 1140-1152. (C1)
  11. T. Boneh, A. Nicholson, L. Sonenberg (2006). Matilda: A Visual Tool for Modelling with Bayesian Networks. International Journal of Intelligent Systems. 21(11), pp.1127-1150. (C1)
  12. C. Twardy, A.E. Nicholson, K.B. Korb, J. McNeil (2006). Epidemiological Data Mining of Cardiovascular Bayesian Networks. Electronic Journal of Health Informatics. Vol 1,  No. 1. (C1)
  13. J. Sheard, G.S. Lowe, A. Nicholson and J. Ceddia (2003). Tackling Transition: Exposing Secondary School Students to Tertiary IT and Learning. Journal of Information Technology Education, 165-180, 2003. (C1)
  14. D. Albrecht, I. Zukerman and A. Nicholson (1998). Bayesian Models for Keyhole Plan Recognition in an Adventure Game.  In User Modeling and User-Adapted Interaction, Kluwer Academic Publishers, Special Issue on Machine Learning in User Modeling, 8(1-2), pp. 5-47. (C1)
  15. K. Fraser and A. Nicholson (1997). Comparing the impact of two assignment-based teaching methodologies on student programming. Journal of Computer Science Education}, 12(1-2):21 – 26. (C1).
  16. T. Dean, L. Kaelbling, J. Kirman, and A. Nicholson (1995). Planning under Time Constraints in Stochastic Domains. Artificial Intelligence, 76(1-2), 35-74. (C1)
  17. A. E. Nicholson and J. M. Brady (1994).  Dynamic belief networks for discrete monitoring.  IEEE Systems, Man and Cybernetics, 24(11):1593—1610. (C1)
  18. K. B. Korb and A. E. Nicholson (2000) The Essential Roles of Emotion in Cognitive Architecture.  Behavioral and Brain Sciences, 26, 205-206. (C2)

Refereed International Conference Papers

  1. Petitjean, F., Webb, G.I., and Nicholson, A.E. (2013). Scaling log linear analysis to high-dimensional data. Proceedings of the 2013 IEEE International Conference on Data Mining (ICDM’13). (E1)
  2. Wilkinson, L.A.T., Chee, Y.E., Nicholson, A.E., and Quintana-Ascencio, P. An Object-oriented Spatial and Temporal Bayesian Network for Managing Willows in an American Heritage River Catchment. To appear in In Proceedings of Models for Spatial, Temporal and Network Data — A UAI Application Workshop, July 15, Bellevue, WA, USA, 2013. (E1)
  3. Perez-Ariza, C.B., Nicholson, A.E. and Flores, M.J. (2012). Prediction of Coffee Rust Disease Using Bayesian Networks. Proc. of the Sixth European Workshop on Probabilistic Graphical Models (PGM-2012), 19-21 September, 2012, Granada, Spain. (E1)
  4. Nicholson, A., Chee, Y.E. and Quintana-Ascencio, P. (2012), A State-Transition DBN for Management of Willows in an American Heritage River Catchment, Proceedings of the Nineth UAI Bayesian Modeling Applications Workshop, 18 August, 2012.
  5. A E Nicholson, O G Woodberry, S Mascaro, K B Korb, A Moorrees and A Lucas (2011). ABC-BN: A tool for building, maintaining and using Bayesian networks in an environmental management application, Proceedings of the Eighth UAI Bayesian Modeling Applications Workshop, 14 July 2011, CEUR Workshop Proceedings, Aachen Germany, pp. 108-116. (E1)
  6. S Mascaro, A E Nicholson and K B Korb (2011). Anomaly detection in vessel tracks using Bayesian networks, Proceedings of the Eighth UAI Bayesian Modeling Applications Workshop, 14 July 2011, CEUR Workshop Proceedings, Aachen Germany, pp. 99-107. (E1)
  7. Y. Wen, K.B. Korb and A. E. Nicholson. DataZapper (2009). Generating Incomplete Datasets. In ICAART 2009 – Proceedings of the International Conference on Agents and Artificial Intelligence, Porto, Portugal, January 19 – 21, 2009. (E1)
  8. C Thomas, A E Nicholson and B T Hart (2008). Observations from field trials with several elicitation techniques in an ecological domain, Proceedings of the Sixth UAI Bayesian Modelling Applications Workshop, 9 July 2008 to 9 July 2008, CEUR-WS.org, on line, pp. 1-9. (E1)
  9. O G Woodberry, K B Korb and A E Nicholson (2008). Species selection of aging for the sake of diversity, Proceedings of the Eleventh International Conference on the Simulation and Synthesis of Living Systems, 5 August 2008 to 8 August 2008, The MIT Press, London England UK, pp. 710-716. (E1)
  10. P. A. Jimenez, B. Shirinzadeh, A. Nicholson, G. Alici (2007), “Optimal Area Covering using Genetic Algorithms,” in IEEE/ASME International Conference on Advanced Intelligent Mechatronics Zürich, Switzerland 2007, pp1-5. (E1)
  11. C.A. Pollino, O. Woodberry, A.E. Nicholson, K.B. Korb (2005). Parameterising Bayesian Networks: A Case Study in Ecological Risk Assessment. In: V. Kachitvichyysnukul, U. Purintrapiban and P. Utayopas (Eds), Proc. of the 2005 Conference on Simulation and Modelling, Bangkok, Thailand, pp. 289-297. (E1)
  12. A. Tang, Y. Jin, J. Han, A. Nicholson (2005). Predicting change impact in architecture design with Bayesian belief networks. In Proceedings 5th Working IEEE/IFIP Conference on Software Architecture (WICSA 2005), IEEE Computer Society, Los Alamitos CA USA, pp. 67-76.  (Acceptance ratio 16%) (One of 5 best papers) (E1)
  13. O. Woodberry, A.E. Nicholson, K.B. Korb and C. Pollino (2004), “Parameterising Bayesian Networks”, in G. I. Webb and X. Yu (eds). Lecture Notes in Artificial Intelligence,” (Proc. of the 17th Australian Joint Conference on Advances in Artificial Intelligence,AI’04), Springer-Verlag, Berlin, Germany, Vol 3339, pp. 1101-1107. (E1)
  14. J. Bally, T. Boneh, A. E. Nicholson and K. B. Korb (2004). Developing An Ontology for the Meterological Forecasting Process , in R. Meredity, G. Shanks, D. Arnott and S. Carlsson (eds), Proc. of the 2004 IFIP International Conference on Decision Support Systems (DSS 2004), pp. 70-81. (Acceptance ratio 50%). (E1)
  15. K.B. Korb, L.R. Hope, A.E. Nicholson and K. Axnick (2004). Varieties of Causal Intervention, in C. Zhang, H. W. Guesgen and W. K. Yeap (eds), Lecture Notes in Artificial Intelligence, (Proc. of the 8th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2004), Springer-Verlag, Berlin, Germany, Vol. 3157, pp. 322-331. (C1 (LNAI))
  16. T. Wilkin, A. Nicholson and T. Dix (2004). A Probabilistic prediction-based replanning architecture for a UAV. Proc. of the 5th Symposium on Intelligent Autonomous Vehicles (IAV-2004). (E1)
  17. K. Stacey, E. Sonenberg, A.E. Nicholson, T. Boneh and V. Steinle (2003). A Teaching Model Exploiting Cognitive Conflict Driven by a Bayesian Network , in P. Brusilovsky, A. Corbett and F. de Rosis (eds), Lecture Notes in Artificial Intelligence (Proc. of the 9th International Conference on User Modelling, UM2003), Springer-Verlag, Berlin, Germany, ISSN: 0302-9743, Vol 2702, pp. 352-362. (C1 (LNAI))
  18. S. Mascaro, K.B. Korb and A.E. Nicholson (2002). ALife Investigation of Parental Investment in Reproductive Strategies, Proc. of the 8th International Conference on the Simulation and Synthesis of Living Systems (ALIFE VIII), (pp. 120-132). (E1)
  19. A.E. Bud, D.W. Albrecht, A.E. Nicholson and I. Zukerman (2001). Playing ‘invisible chess’ with information-theoretic advisors, Proc. of the 2001 AAAI Spring Symposium on Game Theoretic and Decision Theoretic Agents (GTDT 2001), CA, USA, pp. 6-15. (E1)
  20. R. Kennett, K. Korb and A. Nicholson (2001). Sea breeze prediction using Bayesian networks, Lecture Notes in Artificial Intelligence, (2001), (Proc. of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining – PAKDD’01), Springer-Verlag, Berlin, Germany, vol 2035, pp. 148-153. (E1)
  21. S. Mascaro, K.B. Korb and A.E. Nicholson (2001). Suicide as an evolutionarily stable strategy. Proc. of the 6th European Conference on Advances in Artificial Life  (ECAL 2001) pp. 120-132. (E1)
  22. A.E. Nicholson, T. Boneh, T. Wilkin, K. Stacey, L. Sonenberg and V. Steinle (2001). A Case Study in Knowledge Discovery and Elicitation in an Intelligent Tutoring Application, in J. Breese (ed), Proc. of the 17th Conference on Uncertainty in Artificial Intelligence (UAI 2001), pp. 386-394. (E1)
  23. M. J. Abrantes and A E Nicholson (2000).  Knowledge-based assembly modelling for assembly sequence planning of mechanical products, In The Eighth International Conference on Manufacturing Engineering (ICME 2000), pages 323-327 (CD-ROM), Sydney, Australia. (E1)
  24. T. Wilkin and A. Nicholson (2000).  Efficient Inference in Dynamic Belief Networks with Variable Temporal Resolution.  In PRICAI’00 — Proceedings of the 6th Pacific Rim International Conference on Artificial Intelligence, pages 264-274, Melbourne, Australia, 2000. (Joint Best Paper Award) (C1 (LNAI))
  25. I. Zukerman, D. Albrecht, A. Nicholson and K. Doktor (2000).  Trading off Granularity against Complexity in Predictive Models for Complex Domains, In PRICAI’00 — Proceedings of the 6th Pacific Rim International Conference on Artificial Intelligence, pages 241-251, Melbourne, Australia. 2000. (C1 (LNAI))
  26. Albrecht, D., Zukerman, I., and Nicholson, A. (1999).  Pre-sending Documents on the WWW: A Comparative Study.  In IJCAI99 — Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, pages 1274-1279, Stockholm, Sweden. (E1)
  27. Bud, A. E., Nicholson, A., Zukerman, I. and Albrecht, D. (1999). A Hybrid Architecture for Strategically Complex Imperfect Information Games. In KES’99 — Proceedings of the Third International Conference on Knowledge-Based Intelligent Information Engineering Systems, Adelaide, Australia. (E1)
  28. Korb K. B., Ann E. Nicholson, Nathalie Jitnah (1999).  Bayesian poker. In Proc. of the 15th International Conference on Uncertainty in Artificial Intelligence, Stockholm, Sweden, pp. 343-350. (E1)
  29. Zukerman, I., Albrecht, D. and Nicholson, A. (1999). Predicting Users’ Requests on the WWW.  In UM99 — The Seventh International Conference on User Modeling, pages 275-284, Banff, Canada.  (Best application paper prize.) (E1)
  30. Zukerman, I., Nicholson, A., and Albrecht, D. (1999).  Evaluation Methods for Learning about Users.  In IJCAI99 Learning about Users Workshop, pages 83-90, Stockholm, Sweden. (E1)
  31. Albrecht, D., Nicholson, A., and Zukerman, I. (1998). Knowledge Acquisition for Goal Prediction in a Multi-User Adventure Game. In PAKDD’98 — Proceedings of the Second Pacific-Asia Conference on Knowledge Discovery and Data Mining, pages 1-12, Melbourne, Lecture Notes in Artificial Intelligence, Springer-Verlag. (C1 (LNAI))
  32. Baum, J. and Nicholson, A. (1998). Dynamic non-uniform abstractions for approximate planning in large structured stochastic domains.  In PRICAI’98 — Proceedings of the 5th Pacific Rim International Conference on Artificial Intelligence, pages 587-598, Singapore, 1998. (Acceptance ratio 25%) (C1 (LNAI))
  33. Jitnah, N. and Nicholson, A. (1998). Belief network inference algorithms: A study of performance based on domain characterization.  Springer LNCS/LNAI Series, No. 1359.  Proceedings of the Pacific Rim International Conference on AI (PRICAI’98): Workshop on Reasoning with Incomplete and Changing Information, pages 169-188, Cairns, Springer-Verlag. (C1 (LNAI))
  34. Nicholson, A. and Jitnah, N. (1998)., Using mutual information to determine relevance in Bayesian networks.  In PRICAI’98 — Proceedings of the 5th Pacific Rim International Conference on Artificial Intelligence, pages 399-410, Singapore, 1998. (Acceptance ratio 25%) (C1 (LNAI))
  35. Nicholson, A. E., Zukerman, I. and Albrecht, D. W. (1998). A Decision-theoretic Approach for Pre-sending Information on the WWW.  In PRICAI’98 — Proceedings of the 5th Pacific Rim International Conference on Artificial Intelligence, pages 575-586, Singapore, 1998. (Acceptance ratio 25%) (C1 (LNAI))
  36. Nicholson, A.E., Zukerman, I and Oliver, C. (1998). Towards a Society of Affect-driven Agents.  In Proceedings of the Twentieth Annual Conference of the Cognitive Science Society, pages 776-781, Madison, Wisconsin. (Acceptance ratio 38%) (E1)
  37. M. J. Abrantes, C. White and A. E. Nicholson (1997). Minimal infeasible sets of connections: a representation for efficient assembly sequence planning (1997).Proceedings, 1997 IEEE International Symposium on Assembly and Task Planning, IEEE, Piscataway NJ USA, 275-280. (E1)
  38. D. W. Albrecht, .I Zukerman, A. E. Nicholson and A. Bud (1997). Towards a Bayesian model for keyhole plan recognition in large domains (1997). CISM Courses and Lectures No. 383. User Modelling. Proceedings of the Sixth International Conference UM97, Springer Wien, New York NY USA, 365-376. (E1)
  39. A. E. Bud and A. E. Nicholson: Scheduling trains with genetic algorithms (1997). In Proc. of The Fourth International Conference on Neural Information Processing (ICONIP’97), pages 1017-1020, Dunedin, New Zealand. (E1)
  40. N. Jitnah, and A. Nicholson (1997a). treenets: A framework for anytime evaluation of belief networks.  In Proceedings of the International Joint Conference on Qualitative and Quantitative Practical Reasoning, pages 350-364, Seminaris, Bad Honnef, Germany. (E1)
  41. N. Jitnah and A. E. Nicholson (1997b). A best-first search method for anytime evaluation of belief networks. In Proc. of The Fourth International Conference on Neural Information Processing (ICONIP’97), pages 600-603, Dunedin, New Zealand. (E1)
  42. A. E. Nicholson and A. Dutta (1997). Intelligent agents for an interactive multi-media game (1997). ICCIMA’97 Proceedings of the International Conference on Computational Intelligence and Multimedia Applications, Watson Ferguson & Company, Brisbane Australia, 76-80. (E1)
  43. A. E. Nicholson (1996). Fall diagnosis using dynamic belief networks. In Proc. of the 4th Pacific Rim International Conf. on Artificial Intelligence (PRICAI-96), Cairns, Australia, August, 1996. (E1)
  44. J. Kirman, A. Nicholson, M. Lejter, E. Santos, and T. Dean (1994). Using goals to find plans with high expected utility. In E. Sandewall and C. Backstrom, editors, Current Trends in AI Planning, pages 158-170, Amsterdam, 1994. IOS Press. (E1)
  45. T. Dean, L. Kaelbling, J. Kirman and A. Nicholson (1993a). Planning with deadlines in stochastic domains.  In Proceedings the 11th National Conference on Artificial Intelligence (AAAI-93), pp. 574–579. American Association for Artificial Intelligence, 1993.  (Honourable mention, Best written paper) (E1)
  46. T. Dean, L. P. Kaelbling, J. Kirman and A. Nicholson (1993b), Deliberation scheduling for time-critical sequential decision making. In Proceedings of the Ninth Conference on Uncertainty in AI, pages 309-316, 1993. (E1)
  47. A. E. Nicholson and J. M. Brady (1992a).  Sensor validation using Dynamic Belief Networks. In Proc. of the 8th International Conference on Uncertainty in Artificial Intelligence, pp. 207-214. (E1)
  48. A. E. Nicholson and J. M. Brady (1992ba).  The data association problem when monitoring robot vehicles using dynamic belief networks.  In Proc. of the 10th European Conf. on Artificial Intelligence (ECAI-92), pages 689–693, 1992. (E1)

Refereed Australian Conference papers

  1. Perez-Ariza, C.B., Nicholson, A.E., Korb, K.B. Mascaro, S. and Hu, C.H., (2012). To appear in Proceedings of the 25th Australasian Joint Conference on Artificial Intelligence (AI’12). Sydney, Australia, 4-7 December 2012. (E1)
  2. O. Woodberry, K.B. Korb  and A.E. Nicholson (2009). Testing Punctuated Equilibrium Theory using Evolutionary Activity Statistics. Artificial Life: Borrowing from Biology, 1 December 2009 to 4 December 2009, Springer-Verlag, Berlin Germany, pp. 86-95. (E1)
  3. S Zandara and A E Nicholson (2009). Square root unscented particle filtering for grid mapping, Proceedings of the 22nd Australasian Joint Conference AI 2009: Advances in Artificial Intelligence, 1 December 2009 to 4 December 2009, Springer-Verlag, Berlin Germany, pp. 121-130. (E1)
  4. R. T. O’Donnell, A.E. Nicholson, B. Han, K.B. Korb, M.J. Alam, L.R. Hope (2006), “Causal Discovery with Prior Information,” In A Sattar and B H Kang (eds), AI 2006: Advances in Artificial Intelligence, (Proc. of the 19th ACS Australian Joint Conference on Artificial Intelligence), Hobart, TAS, Australia, 4-8 December 2006, Springer-Verlag, Germany, pp 1162-1167. (C1)(LNCS))
  5. S. Mascaro, K.B. Korb and A.E. Nicholson (2005). An ALife investigation on the origins of dimorphic parental investments., In Proc. of the Second Australian Conference on Artificial Life (ACAL 2005). Sydney, Australia, 2005. (C1)(LNCS))
  6. O. Woodberry, K. B. Korb  and A. E. Nicholson (2005). The Evolution of Aging. In Proc. of the Second Australian Conference on Artificial Life (ACAL 2005). Sydney, Australia, 2005. (C1)(LNCS))
  7. O. Woodberry, A. E. Nicholson, K. B. Korb and C. Pollino (2004). Parameterising Bayesian Networks, in G. I. Webb and X. Yu (eds). Lecture Notes in Artificial Intelligence, (Proc. of the 17th Australian Joint Conference on Advances in Artificial Intelligence,AI’04), Springer-Verlag, Berlin, Germany, Vol 3339, pp. 1101-1107. (C1)(LNAI))
  8. N. Jitnah. and A. E. Nicholson. (1999). Arc Weights for Approximate Evaluation of Dynamic Belief Networks. In Proceedings of the 12th Australian Joint Conference on Artificial Intelligence, AI’99, pages 393-404, Sydney, Australia (C1) (LNAI))
  9. A. E. Nicholson and K. M. Fraser (1997). Methodologies for teaching new programming languages: A case study teaching LISP, The Proceedings of the Second Australasian Conference on Computer Science Education, ACM, New York NY USA, 84-90. (E1)
  10. A.E. Nicholson (1988). Declarative debugging of the parallel logic programming language GHC. In Proc. of the 11th Australian Computer Science Conference, pages 225–236, 1988. (E1)

Non refereed Conference papers

  1. P Newham, T Boneh, G T Weymouth, R Potts, J Bally, A E Nicholson and K B Korb: Fog forecasting at Melbourne airport using Bayesian networks, Proceedings of the Fourth International Conference on Fog, Fog Collection and Dew, 22 July 2007 to 27 July 2007, Pontificia Universidad Catolica de Chile, Chile, pp. 291-294. (E2)
  2. G T Weymouth, T Boneh, P Newham, J Bally, R Potts, A E Nicholson and K B Korb: Dealing with uncertainty in fog forecasting for major airports in Australia, Proceedings of the Fourth International Conference on Fog, Fog Collection and Dew, 22 July 2007 to 27 July 2007, Pontificia Universidad Catolica de Chile, Chile, pp. 73-76. (E2)
  3. A. E. Bud, D. W. Albrecht, A. E. Nicholson and I. Zukerman (2001). Information-theoretic advisors in invisible chess, Proceedings of the Artificial Intelligence and Statistics 2001 (AISTATS 2001), Florida, USA, Morgan Kaufman Publishers, 2001, pp 157-162. (E3)
  4. A. E. Nicholson and L. Pack Kaelbling (2004). Toward approximate planning in very large stochastic domains. In AAAI Spring Symposium on Decision Theoretic Planning, pages 190 196, Stanford. (E3)
  5. E Dettmann, A E Nicholson, L Sonnenberg, K Stacey and V Steinle (1999). Bayesian reasoning for diagnosing student misconceptions about decimals (extract of paper), in N Foo (ed), Lecture Notes in Artificial Intelligence 1747, Subseries of Lecture Notes in Computer Science, Advanced Topics in Artificial Intelligence, Proceedings of AI’99, Sydney, Australia, 6-10 December, 1999, Springer-Verlag, Berlin, Germany, ISBN: 3-540-66822-5, pp 486-487. (E3)

Reports

  1. S Zandara and A E Nicholson (2009).  Square Root Unscented Particle Filtering for Grid Mapping, Clayton School of Information Technology, Monash University, 24 pp. Technical report 2009/246.
  2. L R Hope, A E Nicholson and K B Korb (2007). TakeHeart II: A tool to support clinical cardiovascular risk assessment, Clayton School of Information Technology, Monash University, Melbourne 16pp. Technical report 2007/209.
  3. R T O’Donnell, A E Nicholson, B Han, K B Korb, M J Alam and L R Hope (2006). Incorporating Expert Elicited Structural Information in the CaMML Causal Discovery Program, Clayton School of Information Technology, Monash University , Melbourne. Technical report 2006/194
  4. O Woodberry, K Korb, A Nicholson (2006). A Simulation Study of the Evolution of Aging, Clayton School of Information Technology, Monash University, Melbourne, 16pp. Technical report 2006/196.
  5. A. Nicholson (2005). An Issues Paper on the Application of Bayesian Networks to UAV Fault Detection, Diagnosis and Prognostics. Consulting Report for DSTO, Jan. 2005.
  6. C R Twardy, A E Nicholson and K B Korb (2005). Knowledge Engineering Cardiovascular Bayesian Networks from the Literature, Clayton School of IT, Monash University, Melbourne. Technical report 2005/170.
  7. C R Twardy, A E Nicholson, K B Korb and J McNeil (2004). Data Mining Cardiovascular Bayesian Networks, School of Computer Science and Software Engineering, Monash University. Technical report 2004/165.
  8. O Woodberry, A E Nicholson, K B Korb and C Pollino (2004). Parameterising Bayesian Networks: A Case Study in Ecological Risk Assessment, School of Computer Science and Software Engineering, Monash University. Technical report 2004/159.
  9. Boneh, T.Nicholson, A. E.Sonenberg, E. K. Stacey and V. Steinle (2003). DecSys: An Intelligent Tutoring System for Decimal Numeration, School of Computer Science and Software Engineering, Monash University. Technical report 2003/134.
  10. L R Hope, A E Nicholson and K B Korb (2002). Knowledge Engineering Tools for Probability Elicitation, School of Computer Science and Software Engineering, Monash University. Technical report 2002/111.
  11. S Mascaro, K B Korb and A E Nicholson (2002). Parental Investment and Reproductive Strategies, School of Computer Science and Software Engineering, Monash University. Technical report 2002/112.
  12. R Kennett, K B Korb and A E Nicholson (2001).  Seabreeze prediction using Bayesian networks: a case study, School of Computer Science and Software Engineering, Monash University. Technical report 2001/86.
  13. S Mascaro, K B Korb and A E Nicholson (2001).   Suicide as an evolutionary stable strategy, School of Computer Science and Software Engineering, Monash University. Technical report 2001/89.
  14. J Baum and A E Nicholson (1998).  Dynamic non-uniform abstractions for approximate planning in large structures stochastic domains, School of Computer Science and Software Engineering, Monash University. Technical report 1998/18.
  15. A E Nicholson, I Zukerman and D W Albrecht (1998). A decision-theoretic approach for pre-sending information on the WWW, School of Computer Science and Software Engineering, Monash University, Melbourne, 12pp. Technical report 1998/15.
  16. D W Albrecht, I Zukerman and A E Nicholson (1997).  Bayesian models for keyhole plan recognition in an adventure game, Dept Computer Science, Monash University. Technical report CS 97/328.
  17. N Jitnah and A E Nicholson (1997).  Weight-directed search for anytime evaluation of belief networks, Dept Computer Science, Monash University. Technical report CS 97/309.
  18. L Sonnenberg and A E Nicholson (1997). Proceedings of the Fourth Australian Women in Computing Workshop, 97/319, Dept Computer Science, Monash University. Technical report CS 97/319.
  19. A. Nicholson and W. Chwieros (1997). An investigation of techniques for improving the computational efficiency of the p-k algorithm for solving flutter equations. Report for DSTO.
  20. A Bud, A E Nicholson and B Chandra (1996).  Scheduling trains with genetic algorithms, Dept Computer Science, Monash Univ. Technical report CS 96/250.
  21. N Jitnah and A E Nicholson (1996).   Belief network inference algorithms: A study of performance based on domain characterisation, Dept of Computer Science, Monash Univ. Technical report CS 96/249.
  22. A E Nicholson (1996).   A case study in dynamic belief networks: Monitoring walking, fall prediction and detection, Dept of Computer Science, Monash Univ. Technical report CS 96/251.
  23. A E Nicholson (1987).  Declarative debugging of the parallel logic programming language GHC. Technical report 87/12, Dept. of Computer Science, University of Melbourne.
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