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Publications about 'machine learning'
Books
  1. Sanjay Jain. Systems that learn : an introduction to learning theory , Learning, development, and conceptual change. MIT Press, Cambridge, Mass., 2nd edition, 1999.
    Note: Sanjay Jain ... [et al.] ill. ; 24 cm A Bradford book.
    Keywords: machine learning, honours reading. [abstract] [download paper ] [bibtex-entry]


  2. Tom M. Mitchell. Machine Learning. McGraw-Hill, New York, 1997.
    Note: Tom M. Mitchell. Includes bibliographical references and indexes. 1. Introduction -- 2. Concept Learning and the General-to-Specific Ordering -- 3. Decision Tree Learning -- 4. Artificial Neural Networks -- 5. Evaluating Hypotheses -- 6. Bayesian Learning -- 7. Computational Learning Theory -- 8. Instance-Based Learning -- 9. Genetic Algorithms -- 10. Learning Sets of Rules -- 11. Analytical Learning -- 12. Combining Inductive and Analytical Learning -- 13. Reinforcement Learning.
    Keywords: machine learning, honours reading. [bibtex-entry]


  3. Gerhard Weiss and Sandip Sen, editors. Adaptation and Learning in Multi-Agent Systems, volume 1042 of Lecture Notes in Computer Science. Springer, 1996.
    Keywords: machine learning, honours reading. [bibtex-entry]


Journal Articles and Chapters
  1. Jiefei Ma, Alessandra Russo, Krysia Broda, and Keith Clark. DARE: A System for Distributed Abductive Reasoning. Autonomous Agents and Multi-Agent Systems, 16(3):271--297, 2008.
    Keywords: abductive logic programming, inductive logic programming, machine learning, honours reading. [bibtex-entry]


  2. Liviu Panait and Sean Luke. Cooperative Multi-Agent Learning: The State of the Art. Autonomous Agents and Multi-Agent Systems, 11(3):387--434, 2005.
    Keywords: machine learning, inductive logic programming, honours reading, agents. [bibtex-entry]


  3. Liviu Panait and Sean Luke. Cooperative Multi-Agent Learning: The State of the Art. Autonomous Agents & Multi-Agent Systems, 11(3):387--434, 2005.
    Keywords: inductive logic programming, machine learning, honours reading. [bibtex-entry]


  4. Joseph Y. Halpern and Daphne Koller. Representation Dependence in Probabilistic Inference. Journal of Artificial Intelligence Research, 21:319--356, 2004.
    Keywords: Bayesian theory, Epistemic logic, machine learning, honours reading. [bibtex-entry]


  5. F. Alonso, M. d'Inverno, D. Kudenko, M. Luck, and J. Noble. Learning in Agents and Multi-Agent Systems. Knowledge Engineering Review, 16(3):277--284, 2001.
    Keywords: machine learning, agents, honours reading. [bibtex-entry]


  6. Christiano Castelfranchi. The theory of social functions: challenges for computational social science and multi-agent learning. Journal of cognitive systems research, 1:5--38, 2001.
    Keywords: cognitive science, machine learning, agents, intentionality, honours reading. [bibtex-entry]


  7. Junling Hu and Michael P. Weliman. Learning about other agents in a dynamic multiagent system. Journal of cognitive systems research, 1:67--79, 2001.
    Keywords: cognitive science, machine learning, agents, honours reading. [bibtex-entry]


  8. Nicolas Lachiche. Abduction and Induction From a Non-Monotonic Reasoning Perspective. In Peter A. Flach and Antonis C. Kakas, editors,Abduction and Induction: Essays on Their Relation and Integration, pages 107--116. Kluwer Academic Publishers, 2000.
    Keywords: abductive logic programming, inductive logic programming, machine learning, honours reading. [bibtex-entry]


  9. Anil K. Jain, M. Narasimha Murty, and Patrick J. Flynn. Data Clustering: A Review. ACM Computing Surveys, 31(3):264--323, 1999.
    Keywords: sensor networks, honours reading, machine learning. [bibtex-entry]


  10. A. R. Pearce and T. Caelli. Interactively matching hand-drawings using induction. Computer Vision and Image Understanding, 73(3):391--403, 1999.
    Keywords: machine learning, graph theory, agentlab. [abstract] [download paper ] [bibtex-entry]


  11. Sandip Sen and Gerhard Weiss. Learning in Multiagent Systems. In Gerhard Weiss, editor,Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence, pages 259--298. MIT Press, Cambridge, MA, USA, 1999.
    Keywords: machine learning, inductive logic programming, honours reading, agents. [bibtex-entry]


  12. D. Waltz. The importance of importance. Ai Magazine, 20(3):18--35, 1999.
    Note: Times Cited: 4 Article English Cited References Count: 20 244dd.
    Keywords: machine learning, Bayesian Theory, cognitive science, honours reading. [abstract] [download paper ] [bibtex-entry]


  13. Gerhard Weiss and Pierre Dillenbourg. What is 'multi' in Multiagent Learning?. In Pierre Dillenbourg, editor,Collaborative learning. Cognitive and computational approaches, pages 64--80. Pergamon Press, 1999.
    Keywords: machine learning, inductive logic programming, honours reading, agents. [bibtex-entry]


  14. David Carmel and Shaul Markovitch. Model-based Learning of Interaction Strategies in Multiagent Systems. Journal of Experimental and Theoretical Artificial Intelligence, 10(3):309--332, 1998.
    Keywords: model theory, machine learning, inductive logic programming, honours reading. [bibtex-entry]


  15. F. Ho and M. Kamel. Learning Coordination Strategies for Cooperative Multiagent Systems. Machine Learning, 33(2 - 3):155--177, 1998.
    Keywords: machine learning, coordination, honours reading. [bibtex-entry]


  16. Michael P. Wellman and Junling Hu. Conjectural Equilibrium in Multiagent Learning. Machine Learning, Volume , Issue , Nov , Pages, 33(2 - 3):179--200, 1998.
    Keywords: machine learning, honours reading. [bibtex-entry]


  17. Hiroko Aibat and Takao Terano. A Computational Model for Distributed Knowledge Systems with Learning Mechanisms. Expert Systems with Applications, 10(3-4):417--427, 1996.
    Keywords: machine learning, honours reading. [bibtex-entry]


  18. J. R. Quinlan. Improved Use of Continuous Attributes in C4.5. Journal of Artificial Intelligence Research, 4:77--90, 1996.
    Keywords: machine learning, minimum message Length, honours reading. [bibtex-entry]


  19. Gerhard Weiss. Adaptation and Learning in Multi-Agent Systems: Some Remarks and a Bibliography. In Gerhard Weiss and Sandip Sen, editors,Adaptation and Learning in Multi-Agent Systems, pages 1--21. Springer Verlag, 1996.
    Keywords: machine learning, honours reading. [bibtex-entry]


  20. Winton Davies and Peter Edwards. Distributed Learning An Agent-Based Approach to Data-Mining. In Diana Gordon, editor,Working Notes of the ICML '95 Workshop on Agents that Learn from Other Agents. Tahoe City, CA, 1995.
    Keywords: machine learning, honours reading. [bibtex-entry]


  21. Manuela Veloso, Jaime Carbonell, Alicia Perez, Daniel Borrajo, Eugene Fink, and Jim Blythe. Integrating Planning and Learning: The PRODIGY Architecture. Journal of Experimental and Theoretical Artificial Intelligence, 7(1):81--120, 1995.
    Keywords: planning, machine learning, honours reading. [bibtex-entry]


  22. Walter F. Bischof and Terry Caelli. Learning Structural Descriptions of Patterns: A New Technique for Conditional Clustering and Rule Generation. Pattern Recognition, 27(5):689--97, 1994.
    Keywords: machine learning, inductive logic programming, honours reading. [bibtex-entry]


  23. Raymond J. Mooney and John M. Zelle. Integrating ILP and EBL. SIGART Bulletin, 5(1):12--21, 1994.
    Keywords: inductive logic programming, machine learning, honours reading. [bibtex-entry]


  24. A. R. Pearce, T. Caelli, and W. F. Bischof. Rulegraphs for graph matching in pattern recognition. Pattern Recognition, 27(9):1231--47, 1994.
    Keywords: graph theory, machine learning, agentlab. [abstract] [download paper ] [bibtex-entry]


  25. A. R. Pearce, T. Caelli, and W. F. Bischof. Learning relational structures: applications in computer vision. Applied Intelligence, 4(3):257--68, 1994.
    Note: Netherlands.
    Keywords: graph theory, machine learning, agentlab. [abstract] [download paper ] [bibtex-entry]


  26. J. R. Quinlan. Learning logical definitions from relations. Machine Learning, 5:239--266, 1990.
    Keywords: inductive logic programming, machine learning, honours reading. [bibtex-entry]


  27. Nicholas S. Flann and Thomas G. Dietterich. A Study of Explanation-Based Methods for Inductive Learning. Machine Learning, 4(2):187--226, 1989.
    Keywords: explanation-based learning, machine learning, honours reading. [bibtex-entry]


  28. David Poole. Explanation and Prediction: An Architecture for Default and Abductive Reasoning. Computational Intelligence, 5(2):97--110, 1989.
    Keywords: explanation-based learning, machine learning, honours reading. [bibtex-entry]


  29. Gerald Dejong and Raymond J. Mooney. Explanation-Based Learning: An Alternative View. Machine Learning, 1(2):145--176, 1986.
    Keywords: explanation-based learning, machine learning, honours reading. [bibtex-entry]


  30. Tom M. Mitchell, Richard M. Keller, and Smadar T. Kedar-Cabelli. Explanation Based Learning A Unifying View. Machine Learning, 1(1):47--80, 1986.
    Keywords: machine learning, explanation-based learning, honours reading. [bibtex-entry]


Conference Proceedings
  1. Manish Kochhal, Loren Schwiebert, and Sandeep Gupta. Role-based hierarchical self organization for wireless ad hoc sensor networks. In WSNA'03, pages 98--108, 2003. ACM.
    Keywords: sensor networks, machine learning, honours reading. [bibtex-entry]


  2. D. Kazakov and D. Kudenko. Machine learning and inductive logic programming for multi-agent systems. In Multi-Agent Systems and Applications, 9th ECCAI Advanced Course ACAI 2001 and Agent Link's 3rd European Agent Systems Summer School, EASSS 2001, , Lecture Notes in Artificial Intelligence, Volume 2086, Prague, Czech Republic, pages 246--270, 2001. Springer Verlag.
    Keywords: inductive logic programming, machine learning, agents, honours reading. [bibtex-entry]


  3. A. R. Pearce and T. Caelli. The CLARET Algorithm. In Research and Development in Knowledge Discovery and Data Mining, Lecture Notes in Artificial Intelligence, volume 1394, pages 407--408, 1998. Springer-Verlag.
    Keywords: graph theory, machine learning, inductive logic programming, agentlab. [bibtex-entry]


  4. A. R. Pearce, T. Caelli, and Simon Goss. On Learning Spatio-Temporal Relational Structures in Two Different Domains. In Computer Vision-ACCV'98, Lecture Notes in Artificial Intelligence, volume 1352-II, pages 551--558, 1998. Springer-Verlag.
    Keywords: machine learning, agentlab. [bibtex-entry]


  5. Adrian Pearce and Terry Caelli. Schematic Interpretation and the CLARET Consolidated Learning Algorithm. In Proceedings of the First International Conference and Knowledge-Based Intelligent Electronic Systems (KES'97), Adelaide, Australia, volume 1, pages 64--71, 1997.
    Keywords: machine learning, agentlab. [bibtex-entry]


  6. Adrian Pearce, Terry Caelli, and Walter Bischof. CLARET: A new Relational Learning Algorithm for Interpretation in Spatial Domains. In Proceedings of the Fourth International Conference on Control, Automation, Robotics and Vision (ICARV'96), Singapore, pages 650--654, 1996.
    Keywords: graph theory, machine learning, inductive logic programming, agentlab. [bibtex-entry]


  7. Adrian Pearce and Terry Caelli. On the efficiency of spatial learning. In Proceedings of the second Asian conference on computer vision 1995 (ACCV95); Singapore, Parkville, Australia, pages 79--82, 1995.
    Keywords: machine learning, agentlab. [bibtex-entry]


  8. Lorenza Saitta. State of the Art in Machine Learning. In The Newsletter of the European Network of Excellence in Machine Learning, 1995.
    Note: Special Issue.
    Keywords: machine learning, honours reading. [bibtex-entry]


  9. Adrian Pearce, Terry Caelli, and Walter Bischof. Rulegraphs for Pattern Recognition. In Proceedings of the First Asian Conference on Computer Vision 1993 (ACCV93); Osaka, Japan, pages 79--82, 1993.
    Keywords: graph theory, machine learning, agentlab. [bibtex-entry]


  10. Adrian Pearce, Terry Caelli, and Walter Bischof. Learning Relational Structures for 2D Pattern and 3D Object Recognition. In Proceedings of the Australian and New Zealand conference on Intelligent Information Systems 1993 (ANZIIS93); Perth , Western Australia, pages 50--54, 1993.
    Keywords: graph theory, machine learning, agentlab. [bibtex-entry]


  11. J. R. Quinlan and R. M. Cameron-Jones. FOIL: A midterm report. In P. B Brazdil, editor, Machine Learning (ECML-93) European Conference on Machine Learning Proceedings; Vienna, Austria, Berlin, Germany, pages 3--20, 1993. Springer-Verlag.
    Keywords: machine learning, inductive logic programming, honours reading. [bibtex-entry]


Thesis
  1. Adrian Pearce. Relational Evidence Theory and Spatial Interpretation Procedures. PhD, School of Computing, Curtin University, 1996.
    Keywords: machine learning, agentlab. [download paper ] [bibtex-entry]


Tehnical Reports
  1. Claude Sammut and Adrian R. Pearce. Scaling up Behavioural Cloning. Technical report September, School of Computer Science and Engineering, University of New South Wales, 1998.
    Keywords: machine learning, agentlab. [bibtex-entry]


  2. Adrian Pearce, Terry Caelli, and Simon Goss. Aeronautical Parser for Spatio-Temporal Rules obtained by Machine Learning. Contract Report for DSTO 1996, Department of Computing, Curtin University, October 1996.
    Keywords: machine learning, simulation, agentlab. [bibtex-entry]


  3. Adrian Pearce and Terry Caelli. A label Compatibility Checking Method for Evidence-Based Classification Systems. Technical Report 1991, Department of Computer Science, Melbourne University, 1991.
    Keywords: machine learning, agentlab. [bibtex-entry]


Miscellaneous
  1. Alejandro Guerra-Hernandez, Amal El Fallah-Seghrouchni, and Henry Soldano. Distributed Learning in Intentional BDI Multi-Agent Systems, 2004.
    Keywords: BDI, inductive logic programming, honours reading, machine learning. [bibtex-entry]



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Bibliography last modified: Fri Aug 6 11:18:02 2010 translated from BibTEX by bibtex2html