# HG changeset patch # User Robert McIntyre # Date 1366563930 0 # Node ID c135b1d0d0bc1145f05817ed6ec613aef3d390f9 # Parent 31814b60093531555d2ebca58f66b11f5ed9f1c5 reviewed social network paper. diff -r 31814b600935 -r c135b1d0d0bc org/ai-journal-review.org --- a/org/ai-journal-review.org Tue Apr 16 13:59:06 2013 +0000 +++ b/org/ai-journal-review.org Sun Apr 21 17:05:30 2013 +0000 @@ -1,12 +1,37 @@ #+title:Interesting Papers in Artificial Intelligence I decided to read all of the /titles/ in the Artificial Intelligence -journal, and found these interesting papers. The entire process took -about 2 hours. +journal, and found these interesting papers. The entire title-reading +process took about 2 hours. * Interesting Concept -Jordi Delgado - Emergence of social conventions in complex networks +- (2002) Jordi Delgado - Emergence of social conventions in complex networks + + Here, "social conventions" means a very specific property of graphs + in the context of game theory. Their social networks are groups of + mindless automotaons which each have a single opinion that can take + the values "A" or "B". They use the "coordination game" payoff + matrix that engourages each pair of agents to agree with each other, + and study various ways the graph can come to 90% of the agents all + believe either "A" or "B". It's probably not useful for actual + social worlds, and there's no simulation of any interesting + environment, but it might be useful for designing protocols, or as a + problem solving method. + + References: + + L.A. Nunes Amaral, A. Scala, M. Barthélémy, H.E. Stanley, Classes + of small-world networks, Proc. Nat. Acad. Sci. 97 (2000) + 11149–11152. + + D.J Watts, S.H. Strogatz, Collective dynamics of small-world + networks, Nature 393 (1998) 440–442. + + Y. Shoham, M. Tennenholtz, On the emergence of social conventions: + Modeling, analysis and simulations, Artificial Intelligence 94 + (1997) 139–166. + +- (1997) Yoav Shoham, Moshe Tennenholtz - On the emergence of social + conventions: modeling, analysis, and simulations + Marcelo A. Falappa, Gabriele Kern-Isberner, Guillermo R. Simari - Explanations, belief revision and defeasible reasoning @@ -66,8 +91,8 @@ Paul Snow - The vulnerability of the transferable belief model to Dutch books -Simon Kasif, Steven Salzberg, David Waltz, John Rachlin, David W. Aha - - A probabilistic framework for memory-based reasoning +Simon Kasif, Steven Salzberg, David Waltz, John Rachlin, David +W. Aha - A probabilistic framework for memory-based reasoning Geoffrey LaForte, Patrick J. Hayes, Kenneth M. Ford - Why Gödel's theorem cannot refute computationalism @@ -95,9 +120,6 @@ Shmuel Onn, Moshe Tennenholtz - Determination of social laws for multi-agent mobilization -Yoav Shoham, Moshe Tennenholtz - On the emergence of social -conventions: modeling, analysis, and simulations - Stuart J. Russell - Rationality and intelligence Hidde de Jong, Arie Rip - The computer revolution in science: steps @@ -151,9 +173,6 @@ Takeo Kanade - From a real chair to a negative chair -Berthold K.P. Horn, B.G. Schunck - “Determining optical flow”: a -retrospective - Harry G. Barrow, J.M. Tenenbaum - Retrospective on “Interpreting line drawings as three-dimensional surfaces” @@ -597,7 +616,61 @@ Larry S. Davis, Azriel Rosenfeld - Cooperating processes for low-level vision: A survey -Berthold K.P. Horn, Brian G. Schunck - Determining optical flow +- (1980) Berthold K.P. Horn, Brian G. Schunck - Determining optical + flow + + Optical flow is an estimation of the movement of brightness + patterns. If the image is "smooth" then optical flow is also an + estimate of the movement of objects in the image (projected onto the + plane of the image). They get some fairly good results on some very + contrived examples. Important point is that calculating optical flow + involves a relaxation process where the velocities of regions of + constant brightness are inferred from the velocities of the edges of + those regions. + + This paper is a lead up to Horn's book, Robot Vision. + + Hexagonal sampling may be a good alternative to rectangular + sampling. + + A reduced version of this algorithm is implemented in hardware in + optical mice to great effect. + + + Hamming, R.W., Numerical Methods for Scientists and Engineers + (McGraw-Hill, New York, 1962). + + Limb, J.O. and Murphy, J.A., Estimating the velocity of moving + images in television signals, Computer Graphics and Image + Processing 4 (4) (1975) 311-327. + + Mersereau, R.M., The processing of hexagonally sampled + two-dimensional signals, Proc. of the IEEE 67 (6) (1979) 930-949. + + +- (1993) Berthold K.P. Horn, B.G. Schunck - “Determining optical flow”: a + retrospective + + Very useful read where Horn criticies his previous paper. + + - Whishes that he distinguished "optical flow" form "motion + field". "Optical flow" is an image property, whilc the "motion + field" is the movement of objects in 3D space. "Optical flow" is a + 2D vector field; the "motion field" is 3D. + - Wished he made the limitations of his algorithm more clear. + - His original paper didn't concern itself with flow segmentation, + which is required to interpret real world images with objects and + a background. + - Thinks that the best thing about the original paper is that it + introduced variational calculus methods into computer vision. + + References: + + + R. Courant and D. Hilbert, Methods of Mathematical Physics + (Interscience, New York, 1937/1953). + + D. Mart, Vision (Freeman, San Francisco, CA, 1982). + + C.M. Thompson, Robust photo-topography by fusing + shape-from-shading and stereo,Ph.D. Thesis, Mechanical Engineering + Department, MIT, Cambridge, MA (1993). + + K. Ikeuchi and B.K.P. Horn, Numerical shape from shading and + occluding boundaries, Artif lntell. 17 (1981) 141-184. Katsushi Ikeuchi, Berthold K.P. Horn - Numerical shape from shading and occluding boundaries @@ -617,6 +690,42 @@ * Cryo! -Kenneth D. Forbus, Peter B. Whalley, John O. Everett, Leo Ureel, Mike -Brokowski, Julie Baher, Sven E. Kuehne - CyclePad: An articulate -virtual laboratory for engineering thermodynamics +- (1999) Kenneth D. Forbus, Peter B. Whalley, John O. Everett, Leo + Ureel, Mike Brokowski, Julie Baher, Sven E. Kuehne - CyclePad: An + articulate virtual laboratory for engineering thermodynamics + + Should learn about thermodynamics, and about "thermal cycles." + http://www.qrg.northwestern.edu/projects/NSF/cyclepad/cyclepad.htm + + This system is more about expressing models and assumtions than + automatically generating them, and as such is similiar to our "math + language" idea. + + It's like a simple circuit modeller, and similar to Dylan's idea of + an online circuit modeler. + + #+begin_quote + We found that if CyclePad did not do the “obvious” propagation in + preference to interpolation, students trusted it less. + #+end_quote + + It's too bad that the paper doesn't mention the shortcommings of the + system. + + + J.O. Everett, Topological inference of teleology: Deriving + function from structure via evidential reasoning, Artificial + Intelligence 113 (1999) 149–202. + + P. Hayes, Naive physics 1: Ontology for liquids, in: J. Hobbs, + R. Moore (Eds.), Formal Theories of the Commonsense World, Ablex, + Norwood, NJ, 1985. + + P. Nayak, Automated modeling of physical systems, Ph.D. Thesis, + Computer Science Department, Stanford University, 1992. + + R.W. Haywood, Analysis of Engineering Cycles: Power, Refrigerating + and Gas Liquefaction Plant, Pergamon Press, 1985. + + R.M. Stallman, G.J. Sussman, Forward reasoning and + dependency-directed backtracking in a system for computer-aided + circuit analysis, Artificial Intelligence 9 (1977) 135–196. + + Dylan should read this, since it concerns his online circuit + analysis idea. + +