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Additional information


Full CV

PhD Thesis (2009): Understanding Language and Attention: brain-based model and neurophysiological experiments. MRC Cognition & Brain Sciences Unit, University of Cambridge (UK).

PhD Thesis (1999): Belief Systems for Persuasive Discourse Planning. Department of Computer Science, University of Durham (UK).

Older Publications (see also http://cambridge.academia.edu/MaxGaragnani)

Book Chapters:

Garagnani, M. (2004) A Framework for Hybrid and Analogical Planning. In Vlahavas, I., & Vrakas, D. (eds), Intelligent Techniques for Planning, Chapter II (pp. 35-88). Hershey (PA): IDEA Group, Inc.

Refereed articles:

  1. Garagnani, M. (2004) A Diagrammatic Meta-Language for Planning Domain Descriptions. In Castillo, L., Borrajo, D., Salido, M.A. & Oddi, A. (Eds.), Planning, Scheduling and Constraint Satisfaction: from Theory to Practice. Frontiers in AI and Applications, 117:129-138. Amsterdam: IOS Press.
  2. Garagnani, M. (2004) A Framework for Hybrid Planning. Research and Development in Intelligent Systems XXI (Proc. of AI-2004), pp. 214-227. London: Springer-Verlag. ISBN 1-85233-907-1 [Earlier version presented at ICAPS'04 Workshop on Connecting Planning Theory with Practice, Whistler (Canada), June '04]
  3. Garagnani, M. (2003) Model-based planning in physical domains using SetGraphs. In Coenen, F., Preece, A., & Macintosh, A. (eds.), Research and Development in Intelligent Systems XX (Proc. of AI-2003), pp. 295-308. Springer Verlag.
  4. Garagnani, M. & Ding, Y. (2003) Model-based Planning for Object-Rearrangement Problems. In Long, D., McDermott, D., & Thiébaux, S. (Eds.), Proc. of the ICAPS-03 Workshop on PDDL, Trento (Italy), June '03. pp. 49-58.
  5. Davidson, M. & Garagnani, M. (2002) Pre-processing planning domains containing Language Axioms. In Grant, T., & Witteveen, C. (eds.), Proc. of the 21st Workshop of the UK Planning and Scheduling SIG (PlanSIG-02), pp. 23-34. Delft (NL), Nov. '02. ISSN 1368-5708.
  6. Garagnani, M., Shastri, L. & Wendelken, C. (2002) A connectionist model of planning as back-chaining search. In Gray, W.D., & Schunn, C.D. (eds.), Proc. of the 24th Annual Conference of the Cognitive Science Society (CogSci '02), pp.345-350. Mahwah (NJ) and London: Lawrence Erlbaum Associates. [Extended version, in Proc. of PlanSIG-01, Edinburgh (UK), Dec. '01]
  7. Garagnani, M. (2000) Extending Graphplan to Domain Axiom Planning. In Garagnani, M. (Ed.) Proc. of PlanSIG-00, pp. 275-276. Milton Keynes (UK), Dec. 2000. ISSN 1368-5708.
  8. Garagnani, M. (2000) A correct algorithm for efficient planning with preprocessed domain axioms. In Bramer, M., Preece, A. & Coenen, F. (eds.), Research and Development in Intelligent Systems XVII (Proc. of ES-2000), pp.363-374. London: Springer-Verlag.
  9. Garagnani, M. (2000) Speaker-hearer beliefs for discourse planning. In Arabnia, H.R. (ed.) Proc. of the Int'nal Conf. on AI (IC-AI 2000), 1009-1015. Las Vegas (NA), June '00. CSREA Press. ISBN 1-892512-57-2
  10. Garagnani, M. (1999) Improving the efficiency of Pre-processed Domain-axiom planning. In Proc. of PlanSIG-99, pp.190-192. Manchester (UK), Dec. '99. ISSN 1368-5708.
  11. Garagnani, M. (1999) A Sound Linear Algorithm for preprocessing planning problems with Language Axioms. Proc. of PlanSIG-99, pp.40-53. Manchester (UK), Dec. '99. ISSN 1368-5708.
  12. Garagnani, M. (1998) Converting Inference Rules into Conditional Effects. Proc. of PlanSIG-98, pp.203-205. Huddersfield (UK), Sep. '98. ISSN 1368-5708.
  13. Garagnani, M. (1998) Belief Systems and Plans for Communication. Proc. of the 15th Int.'nal Congress on Cybernetics, pp.373-378. Namur (Belgium), August '98. ISBN 2-87215-004-8
  14. Garagnani, M., Fox, M. & Long, D.P. (1998) Belief Systems for Conflict Resolution. Proc. of the 13th European Conf. on AI (ECAI-98) - Workshop on Conflicts Among Agents, pp.55-60. Brighton (UK).
  15. Garagnani, M. (1997) Belief Modelling for Discourse Plans. Proc. of PlanSIG-97, pp.55-67. Durham (UK), Dec. '97. ISSN 1368-5708.
  16. Reed, C.A., Long, D.P., Fox, M. & Garagnani, M. (1997) Persuasion as a form of inter-agent negotiation. Lecture Notes in Artificial Intelligence, 1286:120-136 (Proc. of PRICAI-96 Workshop on Distributed Artificial Intelligence, Cairns, Australia, Aug. '96).
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