ISG@Macquarie

        Abhaya Nayak
            Intelligent Systems Group

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Om Shantih! Shantih! Shantih Om!  

Festschrift for Prof Norman Foo

Belief Revision

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Research

 

PhD Scholarships

PhD Students -- Past and Present

About my research

Research Grants

PhD SCHOLARSHIPS

If you are interested in doing PhD research on a topic related to my research interests (see below), feel free to contact me. Please do provide a brief description of the research you would be interested in, as well as a CV. Macquarie University provides a limited number of PhD scholarships on a competitive basis.

PhD Students -- Past and Present

  1. Jandson Ribeiro Santos (PhD. continuing, jointly at University of São Paulo, Brazil)
  2. Kinzang Chhogyal (PhD. Completed: 2016)
  3. Armin Hezart (PhD. Completed: 2015)
  4. Akther Shermin (PhD. Completed: 2013)
  5. Raghav Ramachandran (PhD. Completed: 2012)
  6. Md. Hadi Mashinchi (PhD. Completed: 2012)
  7. Ali Aydin (PhD. Completed: 2012)
  8. Mo'ad Maghaydah (PhD. Completed: 2011)
  9. Mikhail Prokopenko (PhD. Completed: 2002)
  10. Bao Quoc Vo (PhD. Completed at UNSW: 2002)
  11. Rex Kwok (PhD. Completed at UNSW: 1998)
  12. Maurice Pagnucco(PhD. Completed at USyd: 1996)
ABOUT MY RESEARCH

I study the doxastic (that is Intellectualese for belief-related) aspects of intelligent systems. In particular, I study the dynamics of belief systems.

If you search the web for the target string "belief system", most of the sites you will hit would deal with belief systems associated with different religions. The belief systems I am interested in have very little or nothing to do with religions. A belief system, for me, is a formal system for carrying out representation of the beliefs of an agent, and reason from/about them.

A very simplified way of looking at beliefs is the following: given its goals, an agent reasons from its beliefs about its current state and its environment, to what actions it should perform. Thus, given that I want to drive to the air port, and that I believe the most direct route would be very crowded, I might reason and take the action of driving along a back-route. Thus beliefs are intimately connected with actions.

Here is a very rudimentary account of intelligent system. The system can observe its environment. The observations are used to update its beliefs about the environment. Its changed beliefs might affect the actions it wants to take to reach its goals. AND, the actions it performs modifies its environment, whereby new observations mandate modification in its beliefs. Almost any intelligent system can model this scenario. For instance, the thermostat in your refrigerator can be an intelligent system. It makes an observation (temperature); updates its beliefs accordingly (Is it cold enough?), based on its beliefs and the goal (maintain temperature at four degrees), it might perform some action (eg., shut off the refrigerator) that impacts the environment which might lead to different observations.

There are many interesting aspects to this simple scenario.

  1. You might assume that the system in question never makes a faulty observation. In other words, if two instances of the same test result in different observations, then it must have been because the environment has undergone some change in the mean time.
  2. You might make an assumption on the other extreme. That if the later observation differs from the former, it is not because the environment has changed, but because one (or both) of the observations are inaccurate. In other words, the environment is static, and the observations are all potentially faulty.
  3. You can also relax both these assumptions -- you allow the domain to be dynamic and the observations inaccurate.
  4. To enhance the performance of the refrigerator, you might want the thermostat to receive input from five sensors instead of one, the sensors being positioned at different parts of the refrigerator.
  5. There is no reason why all the sensors in the refrigerator will measure temperature alone! You might want some of the sensors to provide humidity information, and the action of the refrigerator depend on its beliefs both about the temperature and the humidity.
As we change the domain, the issues involved get more complicated. But there is room enough for a lot of good research even under idealistic assumptions. Here are some of the related research topics that I am interested in
  • Reasoning under uncertainty and/or inconsistency
  • Logic of Belief Manipulation
  • Dynamics of Trust
  • Causal Reasoning
  • Preference representation and Belief Merging
  • Intelligent Information Assimilation
  • Coalition formation among information agents
  • Ontology Evolution

RESEARCH GRANTS

2018

  1. U of Wollongong (A. Ghose, H. Dam), Macquarie Uni (MA Orgun, AC Nayak). "Self-Governance in Trusted Autonomous Systems", Defence Innovation Network Pilot Project, $108,522.
2017
  1. Sattar, A., A. Nayak, and J. Delgrande. "Dynamics of Causal Knowledge", ARC Discovery Grant, $114,400.
2016
  1. Sattar, A., A. Nayak, and J. Delgrande. "Dynamics of Causal Knowledge", ARC Discovery Grant, $107,400.
  2. Nayak, A. Informed Trust Dynamics, MQ Faculty of Science & Engineering Safety Net Grant Scheme (2016), $10,000.
2015
  1. Sattar, A., A. Nayak, and J. Delgrande. "Dynamics of Causal Knowledge", ARC Discovery Grant, $110,000.
2013
  1. Nayak, A. Eliciting and Refining Causal Knowledge, Macquarie University Safety Net Grant Scheme. 2012, $25,000.
2012
  1. Nayak, A. (project lead), D. Richards, et al.. Academic integrity in Australia - understanding and changing culture and practice, Office for Learning and Teaching (OLT) Strategic Priority Project (2012-13), $227,000.
  2. Nayak, A. Eliciting and Refining Causal Knowledge, Macquarie University Safety Net Grant Scheme. 2012, $25,000.
2010
  1. Dras, M., A. Nayak, et al. Macquarie University - ARC RIBG (2010) Research Infrastructure Block Grant, $60,000.
2009
  1. Orgun, MA, A. Nayak and P. Busch. Formal Foundations of Representation and Maintenance of Procedural Knowledge, Macquarie University Safety Net Grant Scheme (2009), $19,000.
  2. Nayak, A., MA Orgun, et al. Academic Honesty and Assessment Practices at Macquarie University A Pilot Study, Macquarie Faculty of Science Learning & Teaching Grant (2009-10), $5,000.
2008
  1. Nayak, A. and P. Busch, "Formal Foundations for Tacit Knowledge: Elicitation, Representation and Reasoning", Macquarie University Research Development Grant (2008), $24,710.
  2. Zhang, Y., A. Nayak, K. Wang and F. Lin, "Foundations of Nonmonotonic Logic Programming for Complex Knowledge Systems", ARC Discovery Grant (2008), $76,000.
2007
  1. Nayak, A. and P. Busch, "Formal Foundations for Tacit Knowledge: Elicitation, Representation and Reasoning", Macquarie University Research Development Grant (2007), $23,429.
  2. Zhang, Y., A. Nayak, K. Wang and F. Lin, "Foundations of Nonmonotonic Logic Programming for Complex Knowledge Systems", ARC Discovery Grant (2007), $74,000.
  3. Zhang, Y., M. Orgun, A. Nayak, Y. Mu and F. Bao, "Knowledge Based Model Updating for the Correctness of Security Protocols", ARC Discovery Grant (2007), $82,000.
2006
  1. Zhang, Y., A. Nayak, K. Wang and F. Lin, "Foundations of Nonmonotonic Logic Programming for Complex Knowledge Systems", ARC Discovery Grant (2006), $84,000.
  2. Zhang, Y., M. Orgun, A. Nayak, Y. Mu and F. Bao, "Knowledge Based Model Updating for the Correctness of Security Protocols", ARC Discovery Grant (2006), $80,000.
2005
  1. Zhang, Y., M. Orgun, A. Nayak, Y. Mu and F. Bao, "Knowledge Based Model Updating for the Correctness of Security Protocols", ARC Discovery Grant (2005), $122,000.
  2. Nayak, A., N. Foo, A. Ghose and M. Pagnucco, "Intelligent Information Assimilation", ARC Discovery Grant (2005), $55,000.
  3. Pagnucco, M., C. Sammut, A. sattar and A. Nayak, "Real-time high-level cognitive robotics controllers", ARC Discovery Grant (2005), $70,000. (Relinquished.)
2004
  1. Seed-funding for ARC Research Network on Intelligent Applications through the Semantic Web. (2004). $40,000 ($20,000 from the ARC plus $20,000 from several parts of the Macquarie University).
  2. Nayak, A., N. Foo, A. Ghose and M. Pagnucco, "Intelligent Information Assimilation", ARC Discovery Grant (2004), $60,000.
  3. Pagnucco, M., C. Sammut, A. sattar and A. Nayak, "Real-time high-level cognitive robotics controllers", ARC Discovery Grant (2004), $80,000. (Relinquished.)
2003
  1. Nayak, A., N. Foo, A. Ghose and M. Pagnucco, "Intelligent Information Assimilation", ARC Discovery Grant (2003), $69,000.
  2. Pagnucco, M., C. Sammut, A. sattar and A. Nayak, "Real-time high-level cognitive robotics controllers", ARC Discovery Grant (2003), $90,000. (Relinquished.)
  3. Nayak, A., et al Research Infrastructure Block Grant (2003) under DEST, $30,000.
2002 and Before
  1. Nayak, A. and Orgun, M. Macquarie University, MURG (2002) "Information assimilation and smart choice", $6,877.
  2. Nayak A. and Pagnucco M. Macquarie University, Research Development Scheme Grant (previously ARC Small-Grant) 2001. "Discovering Causal Laws Through Under-specified Actions" $12,100.
  3. Nayak, A. Macquarie University, MURG (2001) "Intelligent Information Assimilation and Choice Making Based on Belief Merging Technique" $6,800.
  4. Pisan, Y and Nayak A. Macquarie University, MURG (2001) "Using Multi-Agent Environments Based on Real World Models for Training" $6,500.


2003 Macquarie University