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Maryam Purvis

SetHeight150-Maryam PBS(Texas), MA(Texas), PhD(Otago)
Senior Lecturer

Room 7.11, Otago Business School
Tel +64 3 479 8423
Email maryam.purvis@otago.ac.nz

Background and interests

Dr Maryam Purvis has a background of working as a software engineer in the computer industry in the United States. Her experience includes all phases of software development such as requirement analysis, design, implementation, and testing.

Her current teaching and research interests are in the areas of dynamic modelling of distributed processes, distributed and dynamic workflow systems, coordination of multi-agent systems as well as the structure of social network interactions.

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Academic qualifications

  • PhD. in Information Science from University of Otago, Dunedin, New Zealand (August 1998)
  • MA in Mathematics from University of Texas, Austin, TX, U.S.A (May 1992)
  • Postgraduate Certificate in Tertiary Teaching from University of Otago, Dunedin, New Zealand (August 2003)

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Papers

Supervision

Currently co-supervising

  • Amir Sedigh
  • Sean Lee
  • Marzieh Jahanbazi

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Publications

Afshar Sedigh, A. H., Purvis, M. K., Savarimuthu, B. T. R., Frantz, C. K., & Purvis, M. A. (2020). Impact of different belief facets on agents' decision: A refined cognitive architecture. arXiv. Retrieved from https://arxiv.org/abs/2004.11858

Afshar Sedigh, A. H., Frantz, C. K., Savarimuthu, B. T. R., Purvis, M. K., & Purvis, M. A. (2019). A comparison of two historical trader societies: An agent-based simulation study of English East India Company and New-Julfa. In P. Davidsson & H. Verhagen (Eds.), Multi-agent-based simulation XIX (MABS): Multi-agent-based simulation XIX: Lecture notes in artificial intelligence (Vol. 11463). (pp. 17-31). Cham, Switzerland: Springer. doi: 10.1007/978-3-030-22270-3_2

Lee, S. H.-S., Deng, J. D., Purvis, M. K., Purvis, M., & Peng, L. (2018). An improved PBIL algorithm for optimal coalition structure generation of smart grids. In M. Ganji, L. Rashidi, B. C. M. Fung & C. Wang (Eds.), Trends and applications in knowledge discovery and data mining: Lecture notes in artificial intelligence (Vol. 11154). (pp. 345-356). Cham, Switzerland: Springer. doi: 10.1007/978-3-030-04503-6_33

Yasir, M., Purvis, M., Purvis, M., & Savarimuthu, T. B. R. (2018). Complementary-based coalition formation for energy microgrids. Computational Intelligence. doi: 10.1111/coin.12171

Lee, S. H.-S., Deng, J. D., Purvis, M. K., & Purvis, M. (2018). Hierarchical population-based learning for optimal large-scale coalition structure generation in smart grids. In T. Mitrovic, B. Xue & X. Li (Eds.), Advances in artifical intelligence: Lecture notes in artificial intelligence (Vol. 11320). (pp. 16-28). Cham, Switzerland: Springer. doi: 10.1007/978-3-030-03991-2_2

Edited Book - Research

Purvis, M., & Savarimuthu, B. T. R. (Eds.). (2009). Computer-mediated social networking: Lecture notes in artificial intelligence (Vol. 5322). Berlin, Germany: Springer, 201p. doi: 10.1007/978-3-642-02276-0

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Chapter in Book - Research

Afshar Sedigh, A. H., Frantz, C. K., Savarimuthu, B. T. R., Purvis, M. K., & Purvis, M. A. (2019). A comparison of two historical trader societies: An agent-based simulation study of English East India Company and New-Julfa. In P. Davidsson & H. Verhagen (Eds.), Multi-agent-based simulation XIX (MABS): Multi-agent-based simulation XIX: Lecture notes in artificial intelligence (Vol. 11463). (pp. 17-31). Cham, Switzerland: Springer. doi: 10.1007/978-3-030-22270-3_2

Lee, S. H.-S., Deng, J. D., Purvis, M. K., Purvis, M., & Peng, L. (2018). An improved PBIL algorithm for optimal coalition structure generation of smart grids. In M. Ganji, L. Rashidi, B. C. M. Fung & C. Wang (Eds.), Trends and applications in knowledge discovery and data mining: Lecture notes in artificial intelligence (Vol. 11154). (pp. 345-356). Cham, Switzerland: Springer. doi: 10.1007/978-3-030-04503-6_33

Jahanbazi, M., Frantz, C., Purvis, M., & Purvis, M. (2016). The role of knowledge keepers in an artificial primitive human society: An agent-based approach. In V. Dignum, P. Noriega, M. Sensoy & J. S. Sichman (Eds.), Coordination, organizations, institutions, and norms in agent systems XI (COIN): Lecture notes in artificial intelligence (Vol. 9628). (pp. 154-172). Cham, Switzerland: Springer International. doi: 10.1007/978-3-319-42691-4_9

Frantz, C., Purvis, M. K., Purvis, M. A., Nowostawski, M., & Lewis, N. D. (2015). Fuzzy modeling of economic institutional rules. In A. Sadeghian & H. Tahayori (Eds.), Frontiers of higher order fuzzy sets. (pp. 87-129). New York: Springer.

Jahanbazi, M., Frantz, C., Purvis, M., & Purvis, M. (2015). Building an artificial primitive human society: An agent-based approach. In A. Ghose, N. Oren, P. Telang & J. Thangarajah (Eds.), Coordination, organizations, institutions and norms in agent systems X (COIN): Lecture notes in artificial intelligence (Vol. 9372). (pp. 89-96). Cham, Switzerland: Springer. doi: 10.1007/978-3-319-25420-3_16

Yasir, M., Purvis, M., Purvis, M., & Savarimuthu, B. T. R. (2015). Improving energy outcomes in dynamically formed micro-grid coalitions. In A. Ghose, N. Oren, P. Telang & J. Thangarajah (Eds.), Coordination, organizations, institutions and norms in agent systems X (COIN): Lecture notes in artificial intelligence (Vol. 9372). (pp. 251-267). Cham, Switzerland: Springer. doi: 10.1007/978-3-319-25420-3_16

Farhangian, M., Purvis, M., Purvis, M., & Savarimuthu, B. T. R. (2015). Agent-based modeling of resource allocation in software projects based on personality and skill. In F. Koch, C. Guttmann & D. Busquets (Eds.), Advances in social computing and multiagent systems: Communications in computer and information science (Vol. 541). (pp. 130-146). Cham, The Netherlands: Springer. doi: 10.1007/978-3-319-24804-2_9

Farhangian, M., Purvis, M., Purvis, M., & Savarimuthu, B. T. R. (2015). The effects of temperament and team formation mechanism on collaborative learning of knowledge and skill in short-term projects. In F. Koch, C. Guttmann & D. Busquets (Eds.), Advances in social computing and multiagent systems: Communications in computer and information science (Vol. 541). (pp. 48-65). Cham, The Netherlands: Springer. doi: 10.1007/978-3-319-24804-2_4

Yasir, M., Purvis, M., Purvis, M., & Savarimuthu, B. T. R. (2014). An intelligent learning mechanism for trading strategies for local energy distribution. In S. Ceppi, E. David, V. Podobnik, V. Robu, O. Shehory, S. Stein & I. A. Vetsikas (Eds.), Agent-mediated electronic commerce: Designing trading strategies and mechanisms for electronic markets (LNBIP 187). (pp. 159-170). Cham, Switzerland: Springer. doi: 10.1007/978-3-319-13218-1_12

Farhangian, M., Purvis, M. K., Purvis, M., & Savarimuthu, B. T. R. (2014). Modelling the effects of personality and temperament in small teams. In T. Balke, F. Dignum, M. Birna van Riemsdijk & A. K. Chopra (Eds.), Coordination, organizations, institutions, and norms in agent systems IX (COIN): Lecture notes in artificial intelligence (Vol. 8386). (pp. 25-41). Cham, Switzerland: Springer. doi: 10.1007/978-3-319-07314-9_2

Yasir, M., Purvis, M. K., Purvis, M., & Savarimuthu, B. T. R. (2014). Intelligent battery strategies for local energy distribution. In T. Balke, F. Dignum, M. Birna van Riemsdijk & A. K. Chopra (Eds.), Coordination, organizations, institutions, and norms in agent systems IX (COIN): Lecture notes in artificial intelligence (Vol. 8386). (pp. 63-80). Cham, Switzerland: Springer. doi: 10.1007/978-3-319-07314-9_4

Andrighetto, G., Cranefield, S., Conte, R., Purvis, M., Purvis, M., Savarimuthu, B. T. R., & Villatoro, D. (2013). (Social) norms and agent-based simulation. In S. Ossowski (Ed.), Agreement technologies: Law, governance and technology series (Vol. 8). (pp. 181-189). Dordrecht, The Netherlands: Springer. doi: 10.1007/978-94-007-5583-3_11

Ebadi, T., Purvis, M., & Purvis, M. K. (2012). A Colored Petri Net model to represent the interactions between a set of cooperative agents. In D. Beneventano, Z. Despotovic, F. Guerra, S. Joseph, G. Moro & A. Perreau de Pinninck (Eds.), Agents and peer-to-peer computing: Lecture notes in artificial intelligence (Vol. 6573). (pp. 141-152). Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-31809-2_13

Savarimuthu, S., Purvis, M., & Purvis, M. K. (2012). Altruistic sharing using tags. In D. Beneventano, Z. Despotovic, F. Guerra, S. Joseph, G. Moro & A. Perreau de Pinninck (Eds.), Agents and peer-to-peer computing: Lecture notes in artificial intelligence (Vol. 6573). (pp. 1-12). Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-31809-2_1

Savarimuthu, B. T. R., Purvis, M., & Verhagen, H. (2012). An agent-based simulation of employing social norms in energy conservation in households. In S. Cranefield & I. Song (Eds.), Agent based simulation for a sustainable society and multi-agent smart computing: Lecture notes in artificial intelligence (Vol. 7580). (pp. 16-31). Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-35612-4_2

Savarimuthu, S., Purvis, M., Savarimuthu, B. T. R., & Purvis, M. (2012). Gossip-based self-organising open agent societies. In N. Desai, A. Liu & M. Winikoff (Eds.), Principles and practice of multi-agent systems: Lecture notes in artificial intelligence (Vol. 7057). (pp. 105-120). Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-25920-3_8

Savarimuthu, B. T. R., Cranefield, S., Purvis, M. A., & Purvis, M. K. (2011). Identifying conditional norms in multi-agent societies. In M. de Vos, N. Fornara, J. V. Pitt & G. Vouros (Eds.), Coordination, organizations, institutions, and norms in agent systems VI (COIN): Lecture notes in artificial intelligence (Vol. 6541). (pp. 285-302). Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-21268-0

Savarimuthu, S., Purvis, M., Purvis, M., & Savarimuthu, B. T. R. (2011). Mechanisms for the self-organization of peer groups in agent societies. In T. Bosse, A. Geller & C. M. Jonker (Eds.), Multi-agent-based simulation XI: Lecture notes in artificial intelligence (Vol. 6532). (pp. 93-107). Berlin, Germany: Springer. doi: 10.1007/978-3-642-18345-4_7

Savarimuthu, B. T. R., Cranefield, S., Purvis, M. A., & Purvis, M. K. (2010). Internal agent architecture for norm identification. In J. Padget, A. Artikis, W. Vasconcelos, K. Stathis, V. Torres da Silva, E. Matson & A. Polleres (Eds.), Coordination, organizations, institutions and norms in agent systems V: Lecture notes in artificial intelligence (Vol. 6069). (pp. 241-256). Berlin, Germany: Springer.

Savarimuthu, B. T. R., Cranefield, S., Purvis, M., & Purvis, M. (2010). A data mining approach to identify obligation norms in agent societies. In L. Cao, A. L. C. Bazzan, V. Gorodetsky, P. A. Mitkas, G. Weiss & P. S. Yu (Eds.), Agents and data mining interaction: Lecture notes in computer science (Vol. 5980). (pp. 43-58). Berlin, Germany: Springer. doi: 10.1007/978-3-642-15420-1_5

Savarimuthu, B. T. R., Purvis, M., & Cranefield, S. (2009). Norm emergence in multi-agent societies. In D. Król & N. Thanh Nguyen (Eds.), Intelligence integration in distributed knowledge management. (pp. 195-206). Hershey, PA: Information Science Reference.

Savarimuthu, B. T. R., Purvis, M., Purvis, M., & Cranefield, S. (2009). Social norm emergence in virtual agent societies. In M. Baldoni, T. C. Son, M. B. van Riemsdijk & M. Winikoff (Eds.), Declarative agent languages and technologies VI: Lecture notes in artificial intelligence (Vol. 5397). (pp. 18-28). Berlin, Germany: Springer.

Purvis, M., Ebadi, T., & Savarimuthu, B. T. R. (2009). An agent-based library management system using RFID technology. In D. Król & N. Thanh Nguyen (Eds.), Intelligence integration in distributed knowledge management. (pp. 171-181). Hershey, PA: Information Science Reference.

Savarimuthu, S., Purvis, M., Purvis, M., & Nowostawski, M. (2009). Mechanisms to restrict exploitation and improve societal performance in multi-agent systems. In D. Król & N. Thanh Nguyen (Eds.), Intelligence integration in distributed knowledge management. (pp. 182-194). Hershey, PA: Information Science Reference.

Savarimuthu, B. T. R., Cranefield, S., Purvis, M., & Purvis, M. (2008). Role model based mechanism for norm emergence in artificial agent societies. In J. S. Sichman, J. Padget, S. Ossowski & P. Noriega (Eds.), Coordination, organizations, institutions, and norms in agent systems III: Lecture notes in artificial intelligence (Vol. 4870). (pp. 203-217). Berlin, Germany: Springer. doi: 10.1007/978-3-540-79003-7_15

Purvis, M., Purvis, M., & Savarimuthu, B. T. R. (2008). Facilitating collaboration in a distributed software development environment using P2P architecture. In S. Joseph, Z. Despotovic, M. Gianluca & S. Begamaschi (Eds.), Agents and peer to peer computing: Lecture Notes in Artificial Intelligence (Vol. 4461). (pp. 167-174). Berlin, Germany: Springer. doi: 10.1007/978-3-540-79705-0_16

Savarimuthu, B. T. R., Purvis, M., & Purvis, M. (2006). Creating ontologies for a collaborative multi-agent based workflow system. In R. P. Katarzyniak (Ed.), Ontologies and soft methods in knowledge management. (pp. 201-216). Adelaide, Australia: Advanced Knowledge International.

Purvis, M. A., Savarimuthu, B. T. R., & Purvis, M. K. (2005). Evaluation of a multi-agent based workflow management system modeled using coloured Petri nets. In M. W. Barley & N. Kasabov (Eds.), Intelligent Agents and Multi-Agent Systems: 7th Pacific Rim International Workshop on Multi-Agents. Lecture Notes in Computer Science, Volume 3371. (pp. 206-216). Berlin, Germany: Springer.

Purvis, M. A., Purvis, M. K., Haidar, A., & Savarimuthu, B. T. R. (2005). A distributed workflow system with autonomous components. In M. W. Barley & N. Kasabov (Eds.), Intelligent agents and multi-agent systems: 7th Pacific Rim International Workshop on Multi-Agents. Lecture Notes in Computer Science, Volume 3371. (pp. 193-205). Berlin, Germany: Springer.

Purvis, M. K., Cranefield, S., Nowostawski, M., & Purvis, M. A. (2004). Multi-agent system interaction protocols in a dynamically changing environment. In T. A. Wagner (Ed.), An application science for multi-agent systems. (pp. 95-112). Boston: Kluwer Academic.

Savarimuthu, B. T. R., & Purvis, M. A. (2004). A collaborative multi-agent based workflow system. In M. G. Negoita, R. J. Howlett & L. C. Jain (Eds.), LNAI 3214: Knowledge-based intelligent information and engineering systems: 8th International Conference. (pp. 1187-1193). Berlin: Springer.

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Journal - Research Article

Yasir, M., Purvis, M., Purvis, M., & Savarimuthu, T. B. R. (2018). Complementary-based coalition formation for energy microgrids. Computational Intelligence. doi: 10.1111/coin.12171

Yasir, M., Purvis, M., Purvis, M., & Savarimuthu, B. T. R. (2017). Agent-based modelling of coalition formation in energy micro-grids. International Journal of Agent-Oriented Software Engineering, 5(4), 399-432. doi: 10.1504/IJAOSE.2017.087639

Yasir, M., Purvis, M. K., Purvis, M., & Savarimuthu, B. T. R. (2015). Agent-based community coordination of local energy distribution. AI & Society, 30(3), 379-391. doi: 10.1007/s00146-013-0528-1

Savarimuthu, S., Purvis, M., Purvis, M., & Savarimuthu, B. T. R. (2015). An agent-based simulation for restricting exploitation in electronic societies through social mechanisms. AI & Society, 30(3), 345-358. doi: 10.1007/s00146-013-0529-0

Savarimuthu, B. T. R., Cranefield, S., Purvis, M. A., & Purvis, M. K. (2013). Identifying prohibition norms in agent societies. Artificial Intelligence & Law, 21(1), 1-46. doi: 10.1007/s10506-012-9126-7

Savarimuthu, S., Purvis, M., Purvis, M., & Savarimuthu, B. T. R. (2013). Gossip-based self-organising agent societies and the impact of false gossip. Minds & Machines, 23(4), 419-441. doi: 10.1007/s11023-013-9304-8

Purvis, M. K., & Purvis, M. A. (2012). Institutional expertise in the Service-Dominant logic: Knowing how and knowing what. Journal of Marketing Management, 28(13/14), 1626-1641. doi: 10.1080/0267257X.2012.742454

Deng, J. D., Purvis, M. K., & Purvis, M. A. (2011). Software effort estimation: Harmonizing algorithms and domain knowledge in an integrated data mining approach. International Journal of Intelligent Information Technologies, 7(3), 41-53. doi: 10.4018/jiit.2011070104

Savarimuthu, B. T. R., Cranefield, S., Purvis, M. A., & Purvis, M. K. (2010). Obligation norm identification in agent societies. Journal of Artificial Societies & Social Simulation, 13(4). Retrieved from http://jasss.soc.surrey.ac.uk/13/4/3.html

Ebadi, T., Purvis, M., & Purvis, M. (2010). A framework for facilitating cooperation in multi-agent systems. Journal of Supercomputing, 51(3), 393-417. doi: 10.1007/s11227-009-0372-8

Savarimuthu, B. T. R., Cranefield, S., Purvis, M. K., & Purvis, M. A. (2009). Norm emergence in agent societies formed by dynamically changing networks. Web Intelligence & Agent Systems, 7(3), 223-232. doi: 10.3233/wia-2009-0164

Ehrler, L., Fleurke, M., Purvis, M., & Savarimuthu, B. T. R. (2006). Agent-based workflow management systems (WfMSs) JBees: A distributed and adaptive WfMS with monitoring and controlling capabilities. Information Systems & E-Business Management, 4(1), 5-23.

Purvis, M. A., Savarimuthu, B. T. R., & Purvis, M. K. (2006). Architecture for active and collaborative learning in a distributed classroom environment. Advanced Technology for Learning, 3(4), 225-232.

Purvis, M. K., Hwang, P., Purvis, M. A., Madhavji, N., & Cranefield, S. J. (2001). A practical look at software internationalisation. Journal of Integrated Design & Process Science, 5(3), 79-90.

Purvis, M. K., Purvis, M. A., & Benwell, G. L. (1995). Modelling and simulation of the New Zealand Resource Management Act. Journal of Law & Information Science, 6(2), 181-192.

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Journal - Professional & Other Non-Research Articles

Purvis, M., Savarimuthu, B. T. R., & Purvis, M. (2005). Making classroom teaching and learning an enjoyable experience! Association for Computing Machinery New Zealand Bulletin, 1(2).

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Conference Contribution - Published proceedings: Full paper

Lee, S. H.-S., Deng, J. D., Purvis, M. K., & Purvis, M. (2018). Hierarchical population-based learning for optimal large-scale coalition structure generation in smart grids. In T. Mitrovic, B. Xue & X. Li (Eds.), Advances in artifical intelligence: Lecture notes in artificial intelligence (Vol. 11320). (pp. 16-28). Cham, Switzerland: Springer. doi: 10.1007/978-3-030-03991-2_2

Lee, S. H.-S., Deng, J. D., Peng, L., Purvis, M. K., & Purvis, M. (2017). Top-k merit weighting PBIL for optimal coalition structure generation of smart grids. In D. Liu, S. Xie, Y. Li, D. Zhao & E.-S. M. El-Alfy (Eds.), Neural information processing: Lecture notes in computer science (Vol. 10637). (pp. 171-181). Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-319-70093-9_18

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