SHRUTI: A neurally motivated architecture for rapid, scalable inference

Studies in Computational Intelligence

Volumn 77, Issue , 2008, Pages 183-203

  Shastri, Lokendra ^a  

^a INTERNATIONAL COMPUTER SCIENCE INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 34548136960     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-540-73954-8_8     Document Type: Review

References (50)

1. Stickel, M., Waldinger, R., Chaudhri, V.: A guide to snark. Technical report, Artificial Intelligence Center, SRI International, Menlo Park CA (2000)
2. Kalman, J.: Automated reasoning with Otter. Rinton Press, Princeton NJ (2001)
3. McCune, W.: Otter 3.3 reference manual. Technical Report Technical Memorandum No. 263, Mathematical and Computer Science Division, Argonne National Laboratory, Argonne IL (2003)
4. Chalupsky, H., MacGregor, R., Russ, T.: PowerLoom Manual. Information Sciences Institute, Marina del Rey CA. (2006)
5. Carpenter, P., Just, M.: Reading comprehension as eyes see it. In Just, M., Carpenter, P., eds.: Cognitive Processes in Comprehension. Erlbaum, Marwah NJ (1977)
6. McKoon, G., Ratcliff, R.: Inference during reading. Psychological Review 99 (1992) 440-466
7. Keenan, J., Baillet, S., Brown, P.: The effects of causal cohesion on comprehension and memory. Journal of Verbal Learning and Verbal Behaavior 23 (1984) 115-_126
8. Kintsch, W.: The role of knowledge discourse comprehension: A constructionintegration model. Psychological Review 95 (1988) 163-182
9. Shastri, L., Ajjanagadde, V.: From simple associations to systematic reasoning. Behavioral and Brain Sciences 16 (1993) 417-494
10. Feldman, J.: Dynamic connections in neural networks. Biological Cybernetics 46 (1982) 27-39
11. Smolensky, P.: Tensor product variable binding and the representation of symbolic structures in connectionist systems. Artificial Intelligence 46 (1990) 159-216
12. Plate, T.: Holographic reduced representations. IEEE Transactions on Neural Networks 6 (1995) 623-641
13. Touretzky, D., Hinton, G. Cognitive Science 12 (1988) 423-466
14. Barnden, J.A., Srinivas, K.: Encoding techniques for complex information structures in connectionist systems. Connection Science 3 (1991) 269-315
15. Lange, T., Dyer, M.: High-level inferencing in a connectionist network. Connection Science 1 (1989) 181-217
16. Sun, R.: On variable binding in connectionist networks. Connection Science 4 (1992) 93-124
17. Ajjanagadde, V., Shastri, L.: Efficient inference with multi-place predicates and variables in a connectionist system. In: Proceedings of the Eleventh Conference of the Cognitive Science Society. (1989) 396-403
18. Park, N., Robertson, D., Stenning, K.: An extension of the temporal synchrony approach to dynamic variable binding. Knowledge-Based Systems 8 (1995) 345-358
19. Sougne, J.: Connectionism and the problem of multiple instantiation. Trends in Cognitive Sciences 2 (1998) 183-189
20. Hummel, J., Holyoak, K.: DistributedArepresentations of structure: a theory of analogical access and mapping. Psychological Review 104 (1997) 427-466
21. von der Malsburg, C.: The correlation theory of brain function. Technical Report 81-2, Max-Planck Institute for Biophysical Chemistry, Gottingen Germany (1981)
22. Shastri, L.: Temporal synchrony, dynamic bindings, and shruti - a representational but non-classical model of reflexive reasoning. Behavioral and Brain Sciences 19 (1996) 331-337
23. Shastri, L.: Advances in shruti - a neurally motivated model of relational knowledge representation and rapid inference using temporal synchrony. Applied Intelligence 11 (1999) 79-108
24. Shastri, L.: Types and quantifiers in shruti - a connectionist model of rapid reasoning and relational processing. InWerter, S., Sun, R., eds.: Hybrid Information Processing in Adaptive Autonomous Vehicles. Springer-Verlag, Heidelberg Germany (2000) 28-45
25. Mani, D., Shastri, L.: Reflexive reasoning with multiple-instantiation in a connectionist reasoning system with a type hierarchy. Connection Science 5 (1993) 205-242
26. Shastri, L., Wendelken, C.: Seeking coherent explanations - a fusion of structured connectionism, temporal synchrony, and evidential reasoning. In: Proceedings of the Twenty-Second Conference of the Cognitive Science Society, Philadelphia PA (2000)
27. Wendelken, C., Shastri, L.: Probabilistic inference and learning in a connectionist causal network. In: Proceedings of the Second International Symposium on Neural Computation, Berlin Germany (2000)
28. Wendelken, C., Shastri, L.: Combining belief and utility in a structured connectionist agent architecture. In: Proceedings of the Twenty-Fourth Annual Conference of the Cognitive Science Society, Fairfax VA (2002)
29. Shastri, L., Grannes, D.: A connectionist treatment of negation and inconsistency. In: Proceedings of the Eighteenth Conference of the Cognitive Science Society. (1996)
30. Shastri, L., Grannes, D., Narayanan, S., Feldman, J.: A connectionist encoding of parameterized schemas and reactive plans. Technical Report TR-02-008, International Computer Science Institute, Berkeley, California, 94704 (2002)
31. Pearl, J.: Probabilistic Reasoning in Intelligent Systems. Morgan Kaufmann, San Francisco CA (1988)
32. Bellman, R.: Dynamic Programming. Princeton University Press, Princeton NJ (1957)
33. Thompson, B., Cohen, M.: Naturalistic decision making and models of computational intelligence. Neural Computing Surveys 2 (1999) 26-28
34. Shastri, L.: Episodic memory trace formation in the hippocampal system: a model of cortico-hippocampal interactions. Technical Report TR-01-004, International Computer Science Institute, Berkeley, California, 94704 (2001)
35. Shastri, L.: Episodic memory and cortico-hippocampal interactions. Trends in Cognitive Sciences 6 (2002) 162-168
36. Bliss, T., CollingridgL, G.: A synaptic model of memory: long-term potentiation in the hippocampus. Nature 361 (1993) 31-39
37. Shastri, L.: A computationally efficient abstraction of long-term potentiation. Neurocomputing 44-46 (2002) 33-41
38. Bi, G., Poo, M.: Synaptic modification by correlated activity: Hebb's postulate revisited. Annual review of neuroscience 24 (2001) 139-166
39. Wickelgren, W.A.: Learning and Memory. Prentice Hall, Englewood Cliffs NJ (1977)
40. Sowa, J., ed.: Principles of Semantic Networks. Morgan Kaufmann, San Francisco (1991)
41. Jordan, M., ed.: Learning in Graphical Models. MIT Press, Cambridge MA (1998)
42. Quillian, M.: Semantic memory. In Minsky, M., ed.: Semantic Information Processing. MIT Press, Cambridge MA (1968) 227-270
43. Fahlman, S.: NETL: A System for Representing and Using Real-World Knowledge. MIT Press, Cambridge MA (1979)
44. Charniak, E.: Passing markers: A theory of contextual influence in language comprehension. Cognitive Science 7 (1983) 171-190
45. Hendler, J.: Integrating marker-passing anA problem solving: a spreading activation approach to improved choice in problem solving. Erlbaum, Marwah NJ (1987)
46. Henderson, J.: Connectionist syntactic parsing using temporal variable binding. Journal of Psycholinguistic Research 23 (1994) 353-379
47. Shastri, L.: A computational model of tractable reasoning - taking inspiration from cognition. In: Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, Chambery France (1993) 202-207
48. Mani, D.: The design and implementation of massively parallel knowledge representation and reasoning systems: A connectionist approach. PhD thesis, University of Pennsylvania (1995)
49. Shastri, L., Mani, D.: Massively parallel knowledge representation and reasoning: Taking a cue from the brain. In Geller, J., Kitano, H., Suttner, C., eds.: Parallel Processing for Artificial Intelligence 3. Elseveir Science, Amsterdam Netherland (1997) 3-40
50. McIlraith, S., Amir, E.: Theorem proving with structured theories. In: Proc. of the Seventeenth International Joint Conference on Artificial Intelligence, Seattle WA (2001)