Case-based reasoning in transfer learning

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5650 LNAI, Issue , 2009, Pages 29-44

  Aha, David W ^a   Molineaux, Matthew ^b   Sukthankar, Gita ^c  

^a NAVAL RESEARCH LABORATORY   (United States)

^b KNEXUS RESEARCH CORPORATION   (United States)

^c University of Central Florida   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALTERNATIVE APPROACH; CONTROL TASK; TASK LEARNING; TRANSFER LEARNING;

EDUCATION; REINFORCEMENT; TARGETS; THERMOLUMINESCENCE;

CASE BASED REASONING;

EID: 70350350697     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-02998-1_4     Document Type: Conference Paper

References (34)

1. Blaylock, N., Allen, J.: Fast hierarchical goal schema recognition. In: Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 796-801. AAAI Press, Boston (2006)
2. Bui, H.: A general model for online probabilistic plan recognition. In: Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, pp. 1309-1318. Morgan Kaufmann, Acapulco (2002)
3. Bransford, J.D., Brown, A.L., Cocking, R.R. (eds.): How people learn: Brain, mind, experience, and school. National Academy Press, Washington (2000)
4. Chang, C.-C., Lin, C.-J.: LIBSVM: A library for support vector machines (2001), http://www.csie.ntu.edu.tw/~cjlin/libsvm
5. Fagan, M., Cunningham, P.: Case-based plan recognition in computer games. In: Ashley, K.D., Bridge, D.G. (eds.) ICCBR 2003. LNCS, vol. 2689, pp. 161-170. Springer, Heidelberg (2003)
6. Falkenhainer, B., Forbus, K.D., Gentner, D.: The structure-mapping engine: Algorithm and examples. Artificial Intelligence 41(1), 1-63 (1989)
7. Gentner, D.: The mechanisms of analogical learning. In: Buchanan, B.G., Wilkins, D.C. (eds.) Readings in knowledge acquisition and learning: Automating the construction and improvement of expert systems. Morgan Kaufmann, San Francisco (1993)
8. Goel, A., Bhatta, S.: Design patterns: A unit of analogical transfer in creative design. Advanced Engineering Informatics 18(2), 85-94 (2004)
9. von Hessling, A., Goel, A.: Abstracting reusable cases from reinforcement learning. In: Aha, D.W., Wilson, D.C. (eds.) Computer gaming and simulation environments: Proceedings of the ICCBR Workshop (2005); S. Bruninghaus (ed.) Workshop Proceedings of the Sixth ICCBR. DePaul University, Chicago
10. Hinrichs, T., Forbus, K.: Analogical learning in a turn-based strategy game. In: Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, pp. 853-858. Professional Book Center, Hyderabad (2007)
11. Kautz, H.: A formal theory of plan recognition. Doctoral dissertation, University of Rochester, Rochester, NY (1987)
12. Kerkez, B., Cox, M.T.: Incremental case-based plan recognition with local predictions. International Journal on Artificial Intelligence Tools 12(4), 413-463 (2003)
13. Klenk, M., Forbus, K.D.: Measuring the level of transfer learning by an AP physics problem-solver. In: Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, pp. 446-451. AAAI Press, Vancouver (2007)
14. Kuhlmann, G., Stone, P.: Graph-based domain mapping for transfer learning in general games. In: Kok, J.N., Koronacki, J., Lopez de Mantaras, R., Matwin, S., Mladenič, D., Skowron, A. (eds.) ECML 2007. LNCS, vol. 4701, pp. 188-200. Springer, Heidelberg (2007)
15. Liao, L., Fox, D., Kautz, H.A.: Location-based activity recognition using relational Markov networks. In: Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, pp. 773-778. Professional Book Center, Edinburgh (2005)
16. Liu, Y., Stone, P.: Value-function-based transfer for reinforcement learning using structure mapping. In: Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 415-420. AAAI Press, Boston (2006)
17. López de Mantaras, R., McSherry, D., Bridge, D.G., Leake, D.B., Smyth, B., Craw, S., Falt-ings, B., Maher, M.L., Cox, M.T., Forbus, K.D., Keane, M., Aamodt, A., Watson, I.D.: Retrieval, reuse, revision and retention in case-based reasoning. Knowledge Engineering Review 20(3), 215-240 (2005)
18. Marx, Z., Rosenstein, M.T., Kaelbling, L.P., Dietterich, T.G.: Transfer learning with an ensemble of background tasks. In: Silver, D., Bakir, G., Bennett, K., Caruana, R., Pontil, M., Russell, S., Tadepalli, P. (eds.) Inductive Transfer: 10 Years Later: Papers from the NIPS Workshop, Whistler, BC, Canada (2005), http://iitrl.acadiau.ca/itws05/
19. Molineaux, M., Aha, D.W.: TIELT: A testbed for gaming environments. In: Proceedings of the Twentieth National Conference on Artificial Intelligence, pp. 1690-1691. AAAI Press, Pittsburgh (2005)
20. Molineaux, M., Aha, D.W., Moore, P.: Learning continuous action models in a real-time strategy environment. In: Proceedings of the Twenty-First International FLAIRS Conference, pp. 257-262. AAAI Press, Coconut Grove (2008)
21. Molineaux, M., Aha, D.W., Sukthankar, G.: Beating the defense: Using plan recognition to inform learning agents. To appear in Proceedings of the Twenty-Second International FLAIRS Conference. AAAI Press, Sanibel Island (2009)
22. Natarajan, S., Bui, H.H., Tadepalli, P., Kersting, K., Wong, W.-K.: Logical hierarchical hidden Markov models for modeling user activities. In: Železný, F., Lavrač, N. (eds.) ILP 2008. LNCS, vol. 5194, pp. 192-209. Springer, Heidelberg (2008)
23. Natarajan, S., Tadepalli, P., Fern, A.: A relational hierarchical model for decision-theoretic assistance. In: Blockeel, H., Ramon, J., Shavlik, J., Tadepalli, P. (eds.) ILP 2007. LNCS, vol. 4894, pp. 175-190. Springer, Heidelberg (2008)
24. Perkins, D.N., Salomon, G.: Transfer of learning. In: Husen, T., Postelwhite, T.N. (eds.) International Handbook of Educational Research, pp. 6452-6457. Pergamon Press, Oxford (1994)
25. Raina, R., Ng, A.Y., Koller, D.: Constructing informative priors using transfer learning. In: Proceedings of the Twenty-Third International Conference on Machine Learning, pp. 713-720. ACM, Pittsburgh (2006)
26. Rosenstein, M.T., Marx, Z., Kaelbling, L.P., Dietterich, T.G.: To transfer or not to transfer. In: Silver, D., Bakir, G., Bennett, K., Caruana, R., Pontil, M., Russell, S., Tadepalli, P. (eds.) Inductive Transfer: 10 Years Later: Papers from the NIPS Workshop, Whistler, BC, Canada (2005), http://iitrl.acadiau.ca/itws05/Papers/ITWS10-RosensteinM05-ITWS.pdf
27. Shapiro, D., Könik, T., O'Rorke, P.: Achieving far transfer in an integrated cognitive architecture. In: Proceedings of the Twenty-Third Conference on Artificial Intelligence, pp. 1325-1330. AAAI Press, Chicago (2008)
28. Sharma, M., Holmes, M., Santamaria, J.C., Irani, A., Isbell Jr., C.L., Ram, A.: Transfer learning in real-time strategy games using hybrid CBR/RL. In: Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, Hyderabad, India, pp. 1041-1046 (2007), http://www.aaai.org/ Papers/IJCAI/2007/IJCAI07-168.pdf
29. Simon, H.A.: Search and reasoning in problem solving. Artificial Intelligence 21, 7-29 (1983)
30. Stracuzzi, D.: Memory organization and knowledge transfer. In: Banerjee, B., Liu, Y., Youngblood, G.M. (eds.) Structural Knowledge Transfer for Machine Learning: Papers from the ICML Workshop, Pittsburgh, PA (2006), http://orca.st.usm.edu/~banerjee/icmlws06/
31. Sukthankar, G., Molineaux, M., Aha, D.W.: Recognizing and exploiting opponent intent in Rush Football (Technical Note AIC-09-062). Naval Research Laboratory, Navy Center for Applied Research in Artificial Intelligence, Washington (2008)
32. Sutton, R., Barto, A.: Reinforcement learning: An introduction. MIT Press, Cambridge (1998)
33. Thorndike, E.L., Woodworth, R.S.: The influence of improvement in one mental function upon the efficiency of other functions (I). Psychological Review 8, 247-261 (1901)
34. Vapnik, V.: Statistical learning theory. Wiley & Sons, New York (1998)