Contact details

John Lloyd
School of Computer Science
College of Engineering and Computer Science
Australian National University
Canberra ACT 0200
Australia

+61 2 6125 8633 (Phone)
+61 2 6125 8651 (Fax)

Research interests

Some papers

• K.S. Ng and J.W. Lloyd, "Probabilistic Reasoning in a Classical Logic", Journal of Applied Logic, 7(2), 218-238, 2009. doi:10.1016/j.jal.207.11.008.
• K.S. Ng, J.W. Lloyd, W.T.B. Uther, "Probabilistic Modelling, Inference and Learning using Logical Theories", Annals of Mathematics and Artificial Intelligence, 54, 159-205, 2008. doi:10.1007/s10472-009-9136-7.
• J.W. Lloyd, "Knowledge Representation and Reasoning in Modal Higher-order Logic", 2007.
• J.W. Lloyd and K.S. Ng, "Probabilistic and Logical Beliefs", LADS 2007, LNAI 5118.
• J.W. Lloyd and K.S. Ng, "Reflections on Agent Beliefs", DALT 2007, LNAI 4897.
• J.W. Lloyd and K.S. Ng, "Learning Modal Theories", ILP 2006, LNAI 4455.
• K.S. Ng and J.W. Lloyd, "Predicate Selection for Structural Decision Trees", ILP 2005, LNAI 3625.
• J.W. Lloyd and T.D. Sears, "An Architecture for Rational Agents", DALT 2005, LNAI 3904.
• J.J. Cole, M.J. Gray, J.W. Lloyd, and K.S. Ng, "Personalisation for User Agents", AAMAS 05.
• J.W. Lloyd, "Modal Higher-order Logic for Agents", 2004.
• T. Gärtner, J.W. Lloyd, and P.A. Flach, "Kernels and Distances for Structured Data", Machine Learning, 57(3): 205-232, 2004.
• J.W. Lloyd, "Logic for Learning: Learning Comprehensible Theories from Structured Data", Springer, Cognitive Technologies Series, July 2003.
• J. Cole, J.W. Lloyd, and K.S. Ng, "Symbolic Learning for Adaptive Agents", 2003.
• T. Gärtner, J.W. Lloyd, and P.A. Flach, "Kernels for Structured Data", ILP 2002.
• J.W. Lloyd, "Higher-order Computational Logic", in Computational Logic: From Logic Programming into the Future, A. Kakas and F. Sadri (editors), Springer-Verlag, 2002.
• J.W. Lloyd, "Knowledge Representation, Computation, and Learning in Higher-order Logic".
• J.W. Lloyd, "Predicate Construction in Higher-order Logic", Electronic Transactions on Artificial Intelligence, Vol. 4(2000), Section B, pp. 21-51.
• A.F. Bowers, C. Giraud-Carrier and J.W. Lloyd, "A Knowledge Representation Framework for Inductive Learning".
• A.F. Bowers, C. Giraud-Carrier and J.W. Lloyd, "Classification of Individuals with Complex Structure", ICML2000.
• J.W. Lloyd, "Programming in an Integrated Functional and Logic Programming Language", Journal of Functional and Logic Programming, 1999(3), March 1999.

Possible student projects

• Implementation of a Programming Language for Artificial Intelligence Applications

  Bach is a probabilistic modal functional logic programming language whose features have been strongly influenced by the needs of artificial intelligence applications. A prototype implementation of the language is currently being used, especially for agent applications. However, a more complete and efficient implementation is needed. There are a number of significant research challenges associated with this, including extending state-of-the-art functional programming language implementation techniques to the novel Bach features and providing efficient probabilistic reasoning.

• Bach for Multi-agent Systems

  Bach is a probabilistic modal functional logic programming language whose features have been strongly influenced by the needs of artificial intelligence applications. However, multi-agent system applications typically require more specialised features than are currently provided by the language. This project would involve designing (and implementing, at least in a prototype fashion) such features, including support for typical agent architectures (such as decision-theoretic and BDI). Experimentation with the enhanced language on challenging multi-agent applications would be essential.