Mercurial > cortex
comparison org/ai-journal-review.org @ 384:c135b1d0d0bc
reviewed social network paper.
author | Robert McIntyre <rlm@mit.edu> |
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date | Sun, 21 Apr 2013 17:05:30 +0000 |
parents | 31814b600935 |
children | ff0d8955711e |
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1 #+title:Interesting Papers in Artificial Intelligence | 1 #+title:Interesting Papers in Artificial Intelligence |
2 | 2 |
3 I decided to read all of the /titles/ in the Artificial Intelligence | 3 I decided to read all of the /titles/ in the Artificial Intelligence |
4 journal, and found these interesting papers. The entire process took | 4 journal, and found these interesting papers. The entire title-reading |
5 about 2 hours. | 5 process took about 2 hours. |
6 | 6 |
7 * Interesting Concept | 7 * Interesting Concept |
8 | 8 |
9 Jordi Delgado - Emergence of social conventions in complex networks | 9 - (2002) Jordi Delgado - Emergence of social conventions in complex networks |
10 | |
11 Here, "social conventions" means a very specific property of graphs | |
12 in the context of game theory. Their social networks are groups of | |
13 mindless automotaons which each have a single opinion that can take | |
14 the values "A" or "B". They use the "coordination game" payoff | |
15 matrix that engourages each pair of agents to agree with each other, | |
16 and study various ways the graph can come to 90% of the agents all | |
17 believe either "A" or "B". It's probably not useful for actual | |
18 social worlds, and there's no simulation of any interesting | |
19 environment, but it might be useful for designing protocols, or as a | |
20 problem solving method. | |
21 | |
22 References: | |
23 + L.A. Nunes Amaral, A. Scala, M. Barthélémy, H.E. Stanley, Classes | |
24 of small-world networks, Proc. Nat. Acad. Sci. 97 (2000) | |
25 11149–11152. | |
26 + D.J Watts, S.H. Strogatz, Collective dynamics of small-world | |
27 networks, Nature 393 (1998) 440–442. | |
28 + Y. Shoham, M. Tennenholtz, On the emergence of social conventions: | |
29 Modeling, analysis and simulations, Artificial Intelligence 94 | |
30 (1997) 139–166. | |
31 | |
32 - (1997) Yoav Shoham, Moshe Tennenholtz - On the emergence of social | |
33 conventions: modeling, analysis, and simulations | |
34 | |
10 | 35 |
11 Marcelo A. Falappa, Gabriele Kern-Isberner, Guillermo R. Simari - | 36 Marcelo A. Falappa, Gabriele Kern-Isberner, Guillermo R. Simari - |
12 Explanations, belief revision and defeasible reasoning | 37 Explanations, belief revision and defeasible reasoning |
13 | 38 |
14 Claudio Bettini, X.Sean Wang, Sushil Jajodia - Solving | 39 Claudio Bettini, X.Sean Wang, Sushil Jajodia - Solving |
64 knowledge discovery in science | 89 knowledge discovery in science |
65 | 90 |
66 Paul Snow - The vulnerability of the transferable belief model to | 91 Paul Snow - The vulnerability of the transferable belief model to |
67 Dutch books | 92 Dutch books |
68 | 93 |
69 Simon Kasif, Steven Salzberg, David Waltz, John Rachlin, David W. Aha | 94 Simon Kasif, Steven Salzberg, David Waltz, John Rachlin, David |
70 - A probabilistic framework for memory-based reasoning | 95 W. Aha - A probabilistic framework for memory-based reasoning |
71 | 96 |
72 Geoffrey LaForte, Patrick J. Hayes, Kenneth M. Ford - Why Gödel's | 97 Geoffrey LaForte, Patrick J. Hayes, Kenneth M. Ford - Why Gödel's |
73 theorem cannot refute computationalism | 98 theorem cannot refute computationalism |
74 | 99 |
75 Hiroshi Motoda, Kenichi Yoshida - Machine learning techniques to make | 100 Hiroshi Motoda, Kenichi Yoshida - Machine learning techniques to make |
93 Kurt Ammon - An automatic proof of Gödel's incompleteness theorem | 118 Kurt Ammon - An automatic proof of Gödel's incompleteness theorem |
94 | 119 |
95 Shmuel Onn, Moshe Tennenholtz - Determination of social laws for | 120 Shmuel Onn, Moshe Tennenholtz - Determination of social laws for |
96 multi-agent mobilization | 121 multi-agent mobilization |
97 | 122 |
98 Yoav Shoham, Moshe Tennenholtz - On the emergence of social | |
99 conventions: modeling, analysis, and simulations | |
100 | |
101 Stuart J. Russell - Rationality and intelligence | 123 Stuart J. Russell - Rationality and intelligence |
102 | 124 |
103 Hidde de Jong, Arie Rip - The computer revolution in science: steps | 125 Hidde de Jong, Arie Rip - The computer revolution in science: steps |
104 towards the realization of computer-supported discovery environments | 126 towards the realization of computer-supported discovery environments |
105 | 127 |
148 | 170 |
149 John McDermott - R1 (“XCON”) at age 12: lessons from an elementary | 171 John McDermott - R1 (“XCON”) at age 12: lessons from an elementary |
150 school achiever | 172 school achiever |
151 | 173 |
152 Takeo Kanade - From a real chair to a negative chair | 174 Takeo Kanade - From a real chair to a negative chair |
153 | |
154 Berthold K.P. Horn, B.G. Schunck - “Determining optical flow”: a | |
155 retrospective | |
156 | 175 |
157 Harry G. Barrow, J.M. Tenenbaum - Retrospective on “Interpreting line | 176 Harry G. Barrow, J.M. Tenenbaum - Retrospective on “Interpreting line |
158 drawings as three-dimensional surfaces” | 177 drawings as three-dimensional surfaces” |
159 | 178 |
160 Judea Pearl - Belief networks revisited | 179 Judea Pearl - Belief networks revisited |
595 Thomas O. Binford - Inferring surfaces from images | 614 Thomas O. Binford - Inferring surfaces from images |
596 | 615 |
597 Larry S. Davis, Azriel Rosenfeld - Cooperating processes for low-level | 616 Larry S. Davis, Azriel Rosenfeld - Cooperating processes for low-level |
598 vision: A survey | 617 vision: A survey |
599 | 618 |
600 Berthold K.P. Horn, Brian G. Schunck - Determining optical flow | 619 - (1980) Berthold K.P. Horn, Brian G. Schunck - Determining optical |
620 flow | |
621 | |
622 Optical flow is an estimation of the movement of brightness | |
623 patterns. If the image is "smooth" then optical flow is also an | |
624 estimate of the movement of objects in the image (projected onto the | |
625 plane of the image). They get some fairly good results on some very | |
626 contrived examples. Important point is that calculating optical flow | |
627 involves a relaxation process where the velocities of regions of | |
628 constant brightness are inferred from the velocities of the edges of | |
629 those regions. | |
630 | |
631 This paper is a lead up to Horn's book, Robot Vision. | |
632 | |
633 Hexagonal sampling may be a good alternative to rectangular | |
634 sampling. | |
635 | |
636 A reduced version of this algorithm is implemented in hardware in | |
637 optical mice to great effect. | |
638 | |
639 + Hamming, R.W., Numerical Methods for Scientists and Engineers | |
640 (McGraw-Hill, New York, 1962). | |
641 + Limb, J.O. and Murphy, J.A., Estimating the velocity of moving | |
642 images in television signals, Computer Graphics and Image | |
643 Processing 4 (4) (1975) 311-327. | |
644 + Mersereau, R.M., The processing of hexagonally sampled | |
645 two-dimensional signals, Proc. of the IEEE 67 (6) (1979) 930-949. | |
646 | |
647 | |
648 - (1993) Berthold K.P. Horn, B.G. Schunck - “Determining optical flow”: a | |
649 retrospective | |
650 | |
651 Very useful read where Horn criticies his previous paper. | |
652 | |
653 - Whishes that he distinguished "optical flow" form "motion | |
654 field". "Optical flow" is an image property, whilc the "motion | |
655 field" is the movement of objects in 3D space. "Optical flow" is a | |
656 2D vector field; the "motion field" is 3D. | |
657 - Wished he made the limitations of his algorithm more clear. | |
658 - His original paper didn't concern itself with flow segmentation, | |
659 which is required to interpret real world images with objects and | |
660 a background. | |
661 - Thinks that the best thing about the original paper is that it | |
662 introduced variational calculus methods into computer vision. | |
663 | |
664 References: | |
665 | |
666 + R. Courant and D. Hilbert, Methods of Mathematical Physics | |
667 (Interscience, New York, 1937/1953). | |
668 + D. Mart, Vision (Freeman, San Francisco, CA, 1982). | |
669 + C.M. Thompson, Robust photo-topography by fusing | |
670 shape-from-shading and stereo,Ph.D. Thesis, Mechanical Engineering | |
671 Department, MIT, Cambridge, MA (1993). | |
672 + K. Ikeuchi and B.K.P. Horn, Numerical shape from shading and | |
673 occluding boundaries, Artif lntell. 17 (1981) 141-184. | |
601 | 674 |
602 Katsushi Ikeuchi, Berthold K.P. Horn - Numerical shape from shading | 675 Katsushi Ikeuchi, Berthold K.P. Horn - Numerical shape from shading |
603 and occluding boundaries | 676 and occluding boundaries |
604 | 677 |
605 Andrew P. Witkin - Recovering surface shape and orientation from | 678 Andrew P. Witkin - Recovering surface shape and orientation from |
615 | 688 |
616 Claude R. Brice, Claude L. Fennema - Scene analysis using regions | 689 Claude R. Brice, Claude L. Fennema - Scene analysis using regions |
617 | 690 |
618 * Cryo! | 691 * Cryo! |
619 | 692 |
620 Kenneth D. Forbus, Peter B. Whalley, John O. Everett, Leo Ureel, Mike | 693 - (1999) Kenneth D. Forbus, Peter B. Whalley, John O. Everett, Leo |
621 Brokowski, Julie Baher, Sven E. Kuehne - CyclePad: An articulate | 694 Ureel, Mike Brokowski, Julie Baher, Sven E. Kuehne - CyclePad: An |
622 virtual laboratory for engineering thermodynamics | 695 articulate virtual laboratory for engineering thermodynamics |
696 | |
697 Should learn about thermodynamics, and about "thermal cycles." | |
698 http://www.qrg.northwestern.edu/projects/NSF/cyclepad/cyclepad.htm | |
699 | |
700 This system is more about expressing models and assumtions than | |
701 automatically generating them, and as such is similiar to our "math | |
702 language" idea. | |
703 | |
704 It's like a simple circuit modeller, and similar to Dylan's idea of | |
705 an online circuit modeler. | |
706 | |
707 #+begin_quote | |
708 We found that if CyclePad did not do the “obvious” propagation in | |
709 preference to interpolation, students trusted it less. | |
710 #+end_quote | |
711 | |
712 It's too bad that the paper doesn't mention the shortcommings of the | |
713 system. | |
714 | |
715 + J.O. Everett, Topological inference of teleology: Deriving | |
716 function from structure via evidential reasoning, Artificial | |
717 Intelligence 113 (1999) 149–202. | |
718 + P. Hayes, Naive physics 1: Ontology for liquids, in: J. Hobbs, | |
719 R. Moore (Eds.), Formal Theories of the Commonsense World, Ablex, | |
720 Norwood, NJ, 1985. | |
721 + P. Nayak, Automated modeling of physical systems, Ph.D. Thesis, | |
722 Computer Science Department, Stanford University, 1992. | |
723 + R.W. Haywood, Analysis of Engineering Cycles: Power, Refrigerating | |
724 and Gas Liquefaction Plant, Pergamon Press, 1985. | |
725 + R.M. Stallman, G.J. Sussman, Forward reasoning and | |
726 dependency-directed backtracking in a system for computer-aided | |
727 circuit analysis, Artificial Intelligence 9 (1977) 135–196. | |
728 + Dylan should read this, since it concerns his online circuit | |
729 analysis idea. | |
730 | |
731 |