Mercurial > cortex
view org/ai-journal-review.org @ 384:c135b1d0d0bc
reviewed social network paper.
| author | Robert McIntyre <rlm@mit.edu> |
|---|---|
| date | Sun, 21 Apr 2013 17:05:30 +0000 |
| parents | 31814b600935 |
| children | ff0d8955711e |
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1 #+title:Interesting Papers in Artificial Intelligence3 I decided to read all of the /titles/ in the Artificial Intelligence4 journal, and found these interesting papers. The entire title-reading5 process took about 2 hours.7 * Interesting Concept9 - (2002) Jordi Delgado - Emergence of social conventions in complex networks11 Here, "social conventions" means a very specific property of graphs12 in the context of game theory. Their social networks are groups of13 mindless automotaons which each have a single opinion that can take14 the values "A" or "B". They use the "coordination game" payoff15 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 all17 believe either "A" or "B". It's probably not useful for actual18 social worlds, and there's no simulation of any interesting19 environment, but it might be useful for designing protocols, or as a20 problem solving method.22 References:23 + L.A. Nunes Amaral, A. Scala, M. Barthélémy, H.E. Stanley, Classes24 of small-world networks, Proc. Nat. Acad. Sci. 97 (2000)25 11149–11152.26 + D.J Watts, S.H. Strogatz, Collective dynamics of small-world27 networks, Nature 393 (1998) 440–442.28 + Y. Shoham, M. Tennenholtz, On the emergence of social conventions:29 Modeling, analysis and simulations, Artificial Intelligence 9430 (1997) 139–166.32 - (1997) Yoav Shoham, Moshe Tennenholtz - On the emergence of social33 conventions: modeling, analysis, and simulations36 Marcelo A. Falappa, Gabriele Kern-Isberner, Guillermo R. Simari -37 Explanations, belief revision and defeasible reasoning39 Claudio Bettini, X.Sean Wang, Sushil Jajodia - Solving40 multi-granularity temporal constraint networks42 Alberto Maria Segre, Sean Forman, Giovanni Resta, Andrew Wildenberg -43 Nagging: A scalable fault-tolerant paradigm for distributed search45 Fahiem Bacchus, Xinguang Chen, Peter van Beek, Toby Walsh - Binary46 vs. non-binary constraints48 Jie Cheng, Russell Greiner, Jonathan Kelly, David Bell, Weiru Liu -49 Learning Bayesian networks from data: An information-theory based50 approach52 Kurt Engesser, Dov M. Gabbay - Quantum logic, Hilbert space, revision53 theory55 J.-D. Fouks, L. Signac - The problem of survival from an algorithmic56 point of view58 Catherine Carr - The MIT Encyclopedia of the Cognitive Sciences,59 edited by Robert Wilson and Frank Keil61 Tim Taylor - Christoph Adami, Introduction to Artificial Life63 Gary William Flake - G.W. Flake, The Computational Beauty of Nature65 A.S d'Avila Garcez, K Broda, D.M Gabbay - Symbolic knowledge66 extraction from trained neural networks: A sound approach68 José Hernández-Orallo - Truth from Trash. How Learning Makes Sense by69 Chris Thornton71 Fabio G. Cozman - Credal networks73 Aaron N. Kaplan, Lenhart K. Schubert - A computational model of belief75 Mike Perkowitz, Oren Etzioni - Towards adaptive Web sites: Conceptual76 framework and case study78 Wilhelm Rödder - Conditional logic and the Principle of Entropy80 Christian Vilhelm, Pierre Ravaux, Daniel Calvelo, Alexandre Jaborska,81 Marie-Christine Chambrin, Michel Boniface - Think!: A unified82 numerical–symbolic knowledge representation scheme and reasoning83 system85 Charles L. Ortiz Jr. - A commonsense language for reasoning about86 causation and rational action88 Raúl E. Valdés-Pérez - Principles of human—computer collaboration for89 knowledge discovery in science91 Paul Snow - The vulnerability of the transferable belief model to92 Dutch books94 Simon Kasif, Steven Salzberg, David Waltz, John Rachlin, David95 W. Aha - A probabilistic framework for memory-based reasoning97 Geoffrey LaForte, Patrick J. Hayes, Kenneth M. Ford - Why Gödel's98 theorem cannot refute computationalism100 Hiroshi Motoda, Kenichi Yoshida - Machine learning techniques to make101 computers easier to use103 Aravind K. Joshi - Role of constrained computational systems in104 natural language processing106 Moshe Tennenholtz - On stable social laws and qualitative equilibria108 Michael Arbib - The metaphorical brains110 Andrew Gelsey, Mark Schwabacher, Don Smith - Using modeling knowledge111 to guide design space search113 Márk Jelasity, József Dombi - GAS, a concept on modeling species in114 genetic algorithms116 Randall H. Wilson - Geometric reasoning about assembly tools118 Kurt Ammon - An automatic proof of Gödel's incompleteness theorem120 Shmuel Onn, Moshe Tennenholtz - Determination of social laws for121 multi-agent mobilization123 Stuart J. Russell - Rationality and intelligence125 Hidde de Jong, Arie Rip - The computer revolution in science: steps126 towards the realization of computer-supported discovery environments128 Adnan Darwiche, Judea Pearl - On the logic of iterated belief revision130 R.C. Holte, T. Mkadmi, R.M. Zimmer, A.J. MacDonald - Speeding up131 problem solving by abstraction: a graph oriented approach133 R. Holte, T. Mkadmi, R.M. Zimmer, A.J. McDonald - Speeding up problem134 solving by abstraction: a graph oriented approach136 Raúl E. Valdés-Pérez - A new theorem in particle physics enabled by137 machine discovery139 Dan Roth - On the hardness of approximate reasoning141 Bart Selman, David G. Mitchell, Hector J. Levesque - Generating hard142 satisfiability problems144 Herbert A. Simon - Artificial intelligence: an empirical science146 John K. Tsotsos - Behaviorist intelligence and the scaling problem148 Shigeki Goto, Hisao Nojima - Equilibrium analysis of the distribution149 of information in human society151 Raúl E. Valdés-Pérez - Machine discovery in chemistry: new results153 Stephen W. Smoliar - Artificial life: Christopher G. Langton, ed.155 Yoav Shoham, Moshe Tennenholtz - On social laws for artificial agent156 societies: off-line design158 Barbara Hayes-Roth - An architecture for adaptive intelligent systems160 Bruce Randall Donald - On information invariants in robotics162 Ian P. Gent, Toby Walsh - Easy problems are sometimes hard164 Tad Hogg, Colin P. Williams - The hardest constraint problems: A165 double phase transition167 Yoram Moses, Yoav Shoham - Belief as defeasible knowledge169 Donald Michie - Turing's test and conscious thought171 John McDermott - R1 (“XCON”) at age 12: lessons from an elementary172 school achiever174 Takeo Kanade - From a real chair to a negative chair176 Harry G. Barrow, J.M. Tenenbaum - Retrospective on “Interpreting line177 drawings as three-dimensional surfaces”179 Judea Pearl - Belief networks revisited181 Glenn A. Kramer - A geometric constraint engine183 Fausto Giunchiglia, Toby Walsh - A theory of abstraction185 John L. Pollock - How to reason defeasibly187 Aaron Sloman - The emperor's real mind: Review of Roger Penrose's the188 emperor's new mind: Concerning computers, minds and the laws of189 physics191 Olivier Dordan - Mathematical problems arising in qualitative192 simulation of a differential equation194 Eric Saund - Putting knowledge into a visual shape representation196 Michael Freund, Daniel Lehmann, Paul Morris - Rationality,197 transitivity, and contraposition199 Anthony S. Maida - Maintaining mental models of agents who have200 existential misconceptions202 Henry A. Kautz, Bart Selman - Hard problems for simple default logics204 Mark J. Stefik, Stephen Smoliar - Four reviews of The Society of Mind205 and a response207 Michael G. Dyer - A society of ideas on cognition: Review of Marvin208 Minsky's The Society of Mind210 Matthew Ginsberg - The society of mind: Marvin Minsky212 George N. Reeke Jr - The society of mind: Marvin Minsky214 Stephen W. Smoliar - The society of mind: Marvin Minsky216 Marvin Minsky - Society of mind: A response to four reviews218 Stephen W. Smoliar - How to build a person: A prolegomenon: John219 Pollock221 David Makinson, Karl Schlechta - Floating conclusions and zombie222 paths: Two deep difficulties in the “directly skeptical” approach to223 defeasible inheritance nets225 Donald A. Norman - Approaches to the study of intelligence227 Rodney A. Brooks - Intelligence without representation229 David Kirsh - Today the earwig, tomorrow man?231 Douglas B. Lenat, Edward A. Feigenbaum - On the thresholds of232 knowledge234 Jordan B. Pollack - Recursive distributed representations236 R. Bhaskar, Anil Nigam - Qualitative physics using dimensional237 analysis239 Don F. Beal - A generalised quiescence search algorithm241 Kai-Fu Lee, Sanjoy Mahajan - The development of a world class Othello242 program244 Helmut Horacek - Reasoning with uncertainty in computer chess246 Jeff Shrager - Induction: Process of inference, learning and247 discovery: John H. Holland, Keith J. Holyoak, Richard E. Nisbett, and248 Paul R. Thagard (MIT Press, Cambridge, MA, 1986); 355 pages250 Daniel S. Weld - The psychology of everyday things: Donald A. Norman,251 (Basic Books, New York, 1988); 257 pages, $19.95253 John R. Anderson - A theory of the origins of human knowledge255 G. Tesauro, T.J. Sejnowski - A parallel network that learns to play256 backgammon258 G. Priest - Reasoning about truth260 Donald Perlis - Truth and meaning262 Daniel S. Weld - Women, fire, and dangerous things: George Lakoff,263 (University of Chicago Press, Chicago, IL, 1987); 614 pages, $29.95265 Mark J. Stefik - On book reviews policy and process267 Robert K. Lindsay - The science of the mind: Owen J. Flanagan, Jr.,268 (MIT Press, Cambridge, MA, 1984); 290 pages270 Sheila Rock - On machine intelligence: Donald Michie, 2nd ed. (Ellis271 Horwood, Chichester, United Kingdom, 1986); 265 pages, £29.95273 Stephen W. Smoliar - Epistemology and cognition: A.I. Goldman,274 (Harvard University Press, Cambridge, MA, 1986); ix + 437 pages,275 $27.50277 David Elliot Shaw - On the range of applicability of an artificial278 intelligence machine280 Michael Gordon - Machine intelligence and related topics: An281 information scientist's weekend book: Donald Michie, (Gordon and282 Breach, New York, 1982); 328 pages, $57.75284 Ryszard S. Michalski, Patrick H. Winston - Variable precision logic286 Martin Herman, Takeo Kanade - Incremental reconstruction of 3D scenes287 from multiple, complex images289 vision : June 8–11, 1987, London, United Kingdom291 André Vellino - Artificial intelligence: The very idea: J. Haugeland,292 (MIT Press, Cambridge, MA, 1985); 287 pp.294 Judea Pearl - Fusion, propagation, and structuring in belief networks296 Daniel G. Bobrow - Scientific debate298 Mark Stefik - The AI business: Commercial uses of artificial299 intelligence: P.H. Winston and K.A. Prendergast, (MIT Press,300 Cambridge, MA 1984); 324 pages, $15.95302 Hans Berliner, Carl Ebeling - The SUPREM architecture: A new303 intelligent paradigm305 Donna Reese - Artificial intelligence: P.H. Winston, (Addison-Wesley,306 Reading, MA, 2nd ed., 1984); 527 pages308 Kenneth D. Forbus - Structure and interpretation of computer programs:309 H. Abelson and G.J. Sussman with J. Sussman, (MIT, Cambridge, 1985);310 503 pages312 Chia-Hoang Lee, Azriel Rosenfeld - Improved methods of estimating313 shape from shading using the light source coordinate system315 Daniel G. Bobrow, Patrick J. Hayes - Artificial intelligence — Where316 are we?318 Barbara J. Grosz - Natural-language processing320 Johan De Kleer - How circuits work322 G.D. Ritchie, F.K. Hanna - am: A case study in AI methodology324 Douglas B. Lenat, John Seely Brown - Why am and eurisko appear to work326 Elaine Kant - On the efficient synthesis of efficient programs328 Randall Davis, Reid G. Smith - Negotiation as a metaphor for329 distributed problem solving331 Patrick H. Winston - Learning new principles from precedents and332 exercises334 Paul S. Rosenbloom - A world-championship-level Othello program336 Tomas Lozano-Perez - Robotics338 Tom M. Mitchell - Generalization as search340 Dana S. Nau - The last player theorem342 Hans J. Berliner - Backgammon computer program beats world champion344 Gerald Jay Sussman, Guy Lewis Steele Jr. - Constraints—A language for345 expressing almost-hierarchical descriptions347 Takeo Kanade - A theory of Origami world349 Ria Follett - Synthesising recursive functions with side effects351 John McCarthy - Circumscription—A form of non-monotonic reasoning353 Michael A. Bauer - Programming by examples355 Patrick H. Winston - Learning by creatifying transfer frames357 Alan Bundy - Will it reach the top? Prediction in the mechanics world359 Richard M. Stallman, Gerald J. Sussman - Forward reasoning and360 dependency-directed backtracking in a system for computer-aided361 circuit analysis363 D. Marr - Artificial intelligence—A personal view365 Berthold K.P. Horn - Understanding image intensities367 F. Malloy Brown - Doing arithmetic without diagrams369 Azriel Rosenfeld - The psychology of computer vision: Patrick Henry370 Winston (ed.) McGraw-Hill, New York, 1975, vi+282 pages, $19.50372 R.C.T. Lee - On machine intelligence: D. Michie. Halstead Press, a373 division of John Wiley & Sons, 1974.375 W.W. Bledsoe, Peter Bruell - A man-machine theorem-proving system377 Gary G. Hendrix - Modeling simultaneous actions and continuous378 processes380 Yoshiaki Shirai - A context sensitive line finder for recognition of381 polyhedra383 Kenneth Mark Colby, Franklin Dennis Hilf, Sylvia Weber, Helena C384 Kraemer - Turing-like indistinguishability tests for the validation of385 a computer simulation of paranoid processes387 Aaron Sloman - Interactions between philosophy and artificial388 intelligence: The role of intuition and non-logical reasoning in389 intelligence391 * Story related393 Charles B. Callaway, James C. Lester - Narrative prose generation395 Katja Markert, Udo Hahn - Understanding metonymies in discourse397 Kathleen R. McKeown, Steven K. Feiner, Mukesh Dalal, Shih-Fu Chang -398 Generating multimedia briefings: coordinating language and399 illustration401 Varol Akman - Formalizing common sense: Papers by John McCarthy:402 V. Lifschitz, ed., (Ablex Publishing Corporation, Norwood, NJ, 1990);403 vi+256 pages, hardback, ISBN 0-89391-535-1 (Library of Congress:404 Q335.M38 1989)406 Akira Shimaya - Interpreting non-3-D line drawings408 Adam J. Grove - Naming and identity in epistemic logic part II: a409 first-order logic for naming411 Luc Lismont, Philippe Mongin - A non-minimal but very weak412 axiomatization of common belief414 on integration of natural language and vision processing416 Russell Greiner - Learning by understanding analogies418 * Review Articles420 H.Jaap van den Herik, Jos W.H.M. Uiterwijk, Jack van Rijswijck - Games421 solved: Now and in the future423 Jonathan Schaeffer, H.Jaap van den Herik - Games, computers, and424 artificial intelligence426 Peter A. Flach - On the state of the art in machine learning: A427 personal review429 A.G. Cohn, D. Perlis - “Field Reviews”: A new style of review article430 for Artificial Intelligence432 James Delgrande, Arvind Gupta, Tim Van Allen - A comparison of433 point-based approaches to qualitative temporal reasoning435 Weixiong Zhang, Rina Dechter, Richard E. Korf - Heuristic search in436 artificial intelligence438 Karen Sparck Jones - Information retrieval and artificial intelligence440 Wolfram Burgard, Armin B. Cremers, Dieter Fox, Dirk Hähnel, Gerhard441 Lakemeyer, Dirk Schulz, Walter Steiner, Sebastian Thrun - Experiences442 with an interactive museum tour-guide robot444 Minoru Asada, Hiroaki Kitano, Itsuki Noda, Manuela Veloso - RoboCup:445 Today and tomorrow—What we have learned447 Margaret A. Boden - Creativity and artificial intelligence449 Daniel G. Bobrow, J.Michael Brady - Artificial Intelligence 40 years450 later452 Fangzhen Lin, Hector J. Levesque - What robots can do: robot programs453 and effective achievability455 Melanie Mitchell - L.D. Davis, handbook of genetic algorithms457 Russell Greiner, Adam J. Grove, Alexander Kogan - Knowing what doesn't458 matter: exploiting the omission of irrelevant data460 W. Whitney, S. Rana, J. Dzubera, K.E. Mathias - Evaluating461 evolutionary algorithms463 David S. Touretzky - Neural networks in artificial intelligence:464 Matthew Zeidenberg466 Mark J. Stefik, Stephen W. Smoliar - The commonsense reviews468 Peter Szolovits, Stephen G. Pauker - Categorical and probabilistic469 reasoning in medicine revisited471 Daniel G. Bobrow - Artificial intelligence in perspective: a472 retrospective on fifty volumes of the Artificial Intelligence Journal474 David Kirsh - Foundations of AI: The big issues476 Hector J. Levesque - All I know: A study in autoepistemic logic478 J.T. Schwartz, M. Sharir - A survey of motion planning and related479 geometric algorithms481 Larry S. Davis, Azriel Rosenfeld - Cooperating processes for low-level482 vision: A survey484 Hans J. Berliner - A chronology of computer chess and its literature486 John McCarthy - Artificial intelligence: a paper symposium: Professor487 Sir James Lighthill, FRS. Artificial Intelligence: A General488 Survey. In: Science Research Council, 1973489 * Cortex related (sensory fusion / simulated worlds)491 Alfonso Gerevini, Jochen Renz - Combining topological and size492 information for spatial reasoning494 John Slaney, Sylvie Thiébaux - Blocks World revisited496 Wai K. Yeap, Margaret E. Jefferies - Computing a representation of the497 local environment499 R.P. Loui - On the origin of objects: B.C. Smith's MIT Press,500 Cambridge, MA, 1996. $37.50 (cloth). $17.50 (paper). 440 pages. ISBN501 0-262-69209-0503 Tze Yun Leong - Multiple perspective dynamic decision making505 Cristiano Castelfranchi - Modelling social action for AI agents507 Luc Steels - The origins of syntax in visually grounded robotic agents509 Sebastian Thrun - Learning metric-topological maps for indoor mobile510 robot navigation512 John Haugeland - Body and world: a review of What Computers Still513 Can't Do: A critique of artificial reason (Hubert L. Dreyfus): (MIT514 Press, Cambridge, MA, 1992); liii + 354 pages, $13.95516 David J. Musliner, Edmund H. Durfee, Kang G. Shin - World modeling for517 the dynamic construction of real-time control plans519 Jozsef A. Toth - Reasoning agents in a dynamic world: The frame520 problem: Kenneth M. Ford and Patrick J. Hayes, eds., (JAI Press,521 Greenwich, CT, 1991); 290+xiv pages523 Michael A. Arbib, Jim-Shih Liaw - Sensorimotor transformations in the524 worlds of frogs and robots526 Ingemar J. Cox, John J. Leonard - Modeling a dynamic environment using527 a Bayesian multiple hypothesis approach529 on integration of natural language and vision processing531 Demetri Terzopoulos, Andrew Witkin, Michael Kass - Constraints on532 deformable models:Recovering 3D shape and nonrigid motion534 Bruce R. Donald - A search algorithm for motion planning with six535 degrees of freedom537 Yorick Wilks - Making preferences more active539 * Vision Related541 Azriel Rosenfeld - B. Jähne, H. Haussecker, and P. Geissler, eds.,542 Handbook of Computer Vision and Applications. 1. Sensors and543 Imaging. 2. Signal Processing and Pattern Recognition. 3. Systems and544 Applications546 Thomas F. Stahovich, Randall Davis, Howard Shrobe - Qualitative547 rigid-body mechanics549 Tzachi Dar, Leo Joskowicz, Ehud Rivlin - Understanding mechanical550 motion: From images to behaviors552 Minoru Asada, Eiji Uchibe, Koh Hosoda - Cooperative behavior553 acquisition for mobile robots in dynamically changing real worlds via554 vision-based reinforcement learning and development556 Thomas F. Stahovich, Randall Davis, Howard Shrobe - Generating557 multiple new designs from a sketch559 Ernst D. Dickmanns - Vehicles capable of dynamic vision: a new breed560 of technical beings?562 Thomas G. Dietterich, Richard H. Lathrop, Tomás Lozano-Pérez - Solving563 the multiple instance problem with axis-parallel rectangles565 Rajesh P.N. Rao, Dana H. Ballard - An active vision architecture based566 on iconic representations568 John K. Tsotsos, Scan M. Culhane, Winky Yan Kei Wai, Yuzhong Lai, Neal569 Davis, Fernando Nuflo - Modeling visual attention via selective tuning571 Roger Mohr, Boubakeur Boufama, Pascal Brand - Understanding572 positioning from multiple images574 Andrew Zisserman, David Forsyth, Joseph Mundy, Charlie Rothwell, Jane575 Liu, Nic Pillow - 3D object recognition using invariance577 Naresh C. Gupta, Laveen N. Kanal - 3-D motion estimation from motion578 field580 Damian M. Lyons - Vision, instruction, and action: David Chapman, (MIT581 Press Cambridge, MA, 1991); 295 pages, $35.00, (paperback)583 Yoshinori Suganuma - Learning structures of visual patterns from584 single instances586 Dana H. Ballard - Animate vision588 Raymond Reiter, Alan K. Mackworth - A logical framework for depiction589 and image interpretation591 Ellen Lowenfeld Walker, Martin Herman - Geometric reasoning for592 constructing 3D scene descriptions from images594 Michele Barry, David Cyrluk, Deepak Kapur, Joseph Mundy, Van-Duc595 Nguyen - A multi-level geometric reasoning system for vision597 Alex P. Pentland - Shading into texture599 Brady - Parallelism in Vision601 Jon A. Webb, J.K. Aggarwal - Structure from motion of rigid and602 jointed objects604 Michael Brady - Computer vision606 Takeo Kanade - Recovery of the three-dimensional shape of an object607 from a single view609 Rodney A. Brooks - Symbolic reasoning among 3-D models and 2-D images611 H.K. Nishihara - Intensity, visible-surface, and volumetric612 representations614 Thomas O. Binford - Inferring surfaces from images616 Larry S. Davis, Azriel Rosenfeld - Cooperating processes for low-level617 vision: A survey619 - (1980) Berthold K.P. Horn, Brian G. Schunck - Determining optical620 flow622 Optical flow is an estimation of the movement of brightness623 patterns. If the image is "smooth" then optical flow is also an624 estimate of the movement of objects in the image (projected onto the625 plane of the image). They get some fairly good results on some very626 contrived examples. Important point is that calculating optical flow627 involves a relaxation process where the velocities of regions of628 constant brightness are inferred from the velocities of the edges of629 those regions.631 This paper is a lead up to Horn's book, Robot Vision.633 Hexagonal sampling may be a good alternative to rectangular634 sampling.636 A reduced version of this algorithm is implemented in hardware in637 optical mice to great effect.639 + Hamming, R.W., Numerical Methods for Scientists and Engineers640 (McGraw-Hill, New York, 1962).641 + Limb, J.O. and Murphy, J.A., Estimating the velocity of moving642 images in television signals, Computer Graphics and Image643 Processing 4 (4) (1975) 311-327.644 + Mersereau, R.M., The processing of hexagonally sampled645 two-dimensional signals, Proc. of the IEEE 67 (6) (1979) 930-949.648 - (1993) Berthold K.P. Horn, B.G. Schunck - “Determining optical flow”: a649 retrospective651 Very useful read where Horn criticies his previous paper.653 - Whishes that he distinguished "optical flow" form "motion654 field". "Optical flow" is an image property, whilc the "motion655 field" is the movement of objects in 3D space. "Optical flow" is a656 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 and660 a background.661 - Thinks that the best thing about the original paper is that it662 introduced variational calculus methods into computer vision.664 References:666 + R. Courant and D. Hilbert, Methods of Mathematical Physics667 (Interscience, New York, 1937/1953).668 + D. Mart, Vision (Freeman, San Francisco, CA, 1982).669 + C.M. Thompson, Robust photo-topography by fusing670 shape-from-shading and stereo,Ph.D. Thesis, Mechanical Engineering671 Department, MIT, Cambridge, MA (1993).672 + K. Ikeuchi and B.K.P. Horn, Numerical shape from shading and673 occluding boundaries, Artif lntell. 17 (1981) 141-184.675 Katsushi Ikeuchi, Berthold K.P. Horn - Numerical shape from shading676 and occluding boundaries678 Andrew P. Witkin - Recovering surface shape and orientation from679 texture681 Irwin Sobel - On calibrating computer controlled cameras for682 perceiving 3-D scenes684 P.M. Will, K.S. Pennington - Grid coding: A preprocessing technique685 for robot and machine vision687 M.B. Clowes - On seeing things689 Claude R. Brice, Claude L. Fennema - Scene analysis using regions691 * Cryo!693 - (1999) Kenneth D. Forbus, Peter B. Whalley, John O. Everett, Leo694 Ureel, Mike Brokowski, Julie Baher, Sven E. Kuehne - CyclePad: An695 articulate virtual laboratory for engineering thermodynamics697 Should learn about thermodynamics, and about "thermal cycles."698 http://www.qrg.northwestern.edu/projects/NSF/cyclepad/cyclepad.htm700 This system is more about expressing models and assumtions than701 automatically generating them, and as such is similiar to our "math702 language" idea.704 It's like a simple circuit modeller, and similar to Dylan's idea of705 an online circuit modeler.707 #+begin_quote708 We found that if CyclePad did not do the “obvious” propagation in709 preference to interpolation, students trusted it less.710 #+end_quote712 It's too bad that the paper doesn't mention the shortcommings of the713 system.715 + J.O. Everett, Topological inference of teleology: Deriving716 function from structure via evidential reasoning, Artificial717 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, Refrigerating724 and Gas Liquefaction Plant, Pergamon Press, 1985.725 + R.M. Stallman, G.J. Sussman, Forward reasoning and726 dependency-directed backtracking in a system for computer-aided727 circuit analysis, Artificial Intelligence 9 (1977) 135–196.728 + Dylan should read this, since it concerns his online circuit729 analysis idea.