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changes from conference.
author Robert McIntyre <rlm@mit.edu>
date Mon, 21 Apr 2014 02:11:29 -0400
parents ff0d8955711e
children ebdedb039cbb
rev   line source
rlm@381 1 #+title:Interesting Papers in Artificial Intelligence
rlm@381 2
rlm@383 3 I decided to read all of the /titles/ in the Artificial Intelligence
rlm@384 4 journal, and found these interesting papers. The entire title-reading
rlm@384 5 process took about 2 hours.
rlm@383 6
rlm@381 7 * Interesting Concept
rlm@381 8
rlm@384 9 - (2002) Jordi Delgado - Emergence of social conventions in complex networks
rlm@384 10
rlm@384 11 Here, "social conventions" means a very specific property of graphs
rlm@384 12 in the context of game theory. Their social networks are groups of
rlm@384 13 mindless automotaons which each have a single opinion that can take
rlm@384 14 the values "A" or "B". They use the "coordination game" payoff
rlm@384 15 matrix that engourages each pair of agents to agree with each other,
rlm@384 16 and study various ways the graph can come to 90% of the agents all
rlm@384 17 believe either "A" or "B". It's probably not useful for actual
rlm@384 18 social worlds, and there's no simulation of any interesting
rlm@384 19 environment, but it might be useful for designing protocols, or as a
rlm@384 20 problem solving method.
rlm@384 21
rlm@384 22 References:
rlm@384 23 + L.A. Nunes Amaral, A. Scala, M. Barthélémy, H.E. Stanley, Classes
rlm@384 24 of small-world networks, Proc. Nat. Acad. Sci. 97 (2000)
rlm@384 25 11149–11152.
rlm@384 26 + D.J Watts, S.H. Strogatz, Collective dynamics of small-world
rlm@384 27 networks, Nature 393 (1998) 440–442.
rlm@384 28 + Y. Shoham, M. Tennenholtz, On the emergence of social conventions:
rlm@384 29 Modeling, analysis and simulations, Artificial Intelligence 94
rlm@384 30 (1997) 139–166.
rlm@384 31
rlm@384 32 - (1997) Yoav Shoham, Moshe Tennenholtz - On the emergence of social
rlm@384 33 conventions: modeling, analysis, and simulations
rlm@384 34
rlm@381 35
rlm@381 36 Marcelo A. Falappa, Gabriele Kern-Isberner, Guillermo R. Simari -
rlm@381 37 Explanations, belief revision and defeasible reasoning
rlm@381 38
rlm@381 39 Claudio Bettini, X.Sean Wang, Sushil Jajodia - Solving
rlm@381 40 multi-granularity temporal constraint networks
rlm@381 41
rlm@381 42 Alberto Maria Segre, Sean Forman, Giovanni Resta, Andrew Wildenberg -
rlm@381 43 Nagging: A scalable fault-tolerant paradigm for distributed search
rlm@381 44
rlm@381 45 Fahiem Bacchus, Xinguang Chen, Peter van Beek, Toby Walsh - Binary
rlm@381 46 vs. non-binary constraints
rlm@381 47
rlm@381 48 Jie Cheng, Russell Greiner, Jonathan Kelly, David Bell, Weiru Liu -
rlm@381 49 Learning Bayesian networks from data: An information-theory based
rlm@381 50 approach
rlm@381 51
rlm@381 52 Kurt Engesser, Dov M. Gabbay - Quantum logic, Hilbert space, revision
rlm@381 53 theory
rlm@381 54
rlm@381 55 J.-D. Fouks, L. Signac - The problem of survival from an algorithmic
rlm@381 56 point of view
rlm@381 57
rlm@381 58 Catherine Carr - The MIT Encyclopedia of the Cognitive Sciences,
rlm@381 59 edited by Robert Wilson and Frank Keil
rlm@381 60
rlm@386 61 - Tim Taylor - Christoph Adami, Introduction to Artificial Life
rlm@386 62 References:
rlm@386 63 + M.A. Boden (Ed.), The Philosophy of Artificial Life, Oxford
rlm@386 64 University Press, Oxford, 1996.
rlm@386 65 + C.G. Langton (Ed.), Artificial Life: An Introduction, MIT Press,
rlm@386 66 Cambridge, MA, 1995.
rlm@381 67
rlm@381 68 A.S d'Avila Garcez, K Broda, D.M Gabbay - Symbolic knowledge
rlm@381 69 extraction from trained neural networks: A sound approach
rlm@381 70
rlm@381 71 José Hernández-Orallo - Truth from Trash. How Learning Makes Sense by
rlm@381 72 Chris Thornton
rlm@381 73
rlm@381 74 Fabio G. Cozman - Credal networks
rlm@381 75
rlm@381 76 Aaron N. Kaplan, Lenhart K. Schubert - A computational model of belief
rlm@381 77
rlm@381 78 Mike Perkowitz, Oren Etzioni - Towards adaptive Web sites: Conceptual
rlm@381 79 framework and case study
rlm@381 80
rlm@381 81 Wilhelm Rödder - Conditional logic and the Principle of Entropy
rlm@381 82
rlm@381 83 Christian Vilhelm, Pierre Ravaux, Daniel Calvelo, Alexandre Jaborska,
rlm@381 84 Marie-Christine Chambrin, Michel Boniface - Think!: A unified
rlm@381 85 numerical–symbolic knowledge representation scheme and reasoning
rlm@381 86 system
rlm@381 87
rlm@381 88 Charles L. Ortiz Jr. - A commonsense language for reasoning about
rlm@381 89 causation and rational action
rlm@381 90
rlm@381 91 Raúl E. Valdés-Pérez - Principles of human—computer collaboration for
rlm@381 92 knowledge discovery in science
rlm@381 93
rlm@381 94 Paul Snow - The vulnerability of the transferable belief model to
rlm@381 95 Dutch books
rlm@381 96
rlm@384 97 Simon Kasif, Steven Salzberg, David Waltz, John Rachlin, David
rlm@384 98 W. Aha - A probabilistic framework for memory-based reasoning
rlm@381 99
rlm@381 100 Geoffrey LaForte, Patrick J. Hayes, Kenneth M. Ford - Why Gödel's
rlm@381 101 theorem cannot refute computationalism
rlm@381 102
rlm@381 103 Hiroshi Motoda, Kenichi Yoshida - Machine learning techniques to make
rlm@381 104 computers easier to use
rlm@381 105
rlm@381 106 Aravind K. Joshi - Role of constrained computational systems in
rlm@381 107 natural language processing
rlm@381 108
rlm@381 109 Moshe Tennenholtz - On stable social laws and qualitative equilibria
rlm@381 110
rlm@381 111 Michael Arbib - The metaphorical brains
rlm@381 112
rlm@381 113 Andrew Gelsey, Mark Schwabacher, Don Smith - Using modeling knowledge
rlm@381 114 to guide design space search
rlm@381 115
rlm@381 116 Márk Jelasity, József Dombi - GAS, a concept on modeling species in
rlm@381 117 genetic algorithms
rlm@381 118
rlm@381 119 Randall H. Wilson - Geometric reasoning about assembly tools
rlm@381 120
rlm@381 121 Kurt Ammon - An automatic proof of Gödel's incompleteness theorem
rlm@381 122
rlm@381 123 Shmuel Onn, Moshe Tennenholtz - Determination of social laws for
rlm@381 124 multi-agent mobilization
rlm@381 125
rlm@381 126 Stuart J. Russell - Rationality and intelligence
rlm@381 127
rlm@381 128 Hidde de Jong, Arie Rip - The computer revolution in science: steps
rlm@381 129 towards the realization of computer-supported discovery environments
rlm@381 130
rlm@381 131 Adnan Darwiche, Judea Pearl - On the logic of iterated belief revision
rlm@381 132
rlm@381 133 R.C. Holte, T. Mkadmi, R.M. Zimmer, A.J. MacDonald - Speeding up
rlm@381 134 problem solving by abstraction: a graph oriented approach
rlm@381 135
rlm@381 136 R. Holte, T. Mkadmi, R.M. Zimmer, A.J. McDonald - Speeding up problem
rlm@381 137 solving by abstraction: a graph oriented approach
rlm@381 138
rlm@381 139 Raúl E. Valdés-Pérez - A new theorem in particle physics enabled by
rlm@381 140 machine discovery
rlm@381 141
rlm@381 142 Dan Roth - On the hardness of approximate reasoning
rlm@381 143
rlm@381 144 Bart Selman, David G. Mitchell, Hector J. Levesque - Generating hard
rlm@381 145 satisfiability problems
rlm@381 146
rlm@381 147 Herbert A. Simon - Artificial intelligence: an empirical science
rlm@381 148
rlm@381 149 John K. Tsotsos - Behaviorist intelligence and the scaling problem
rlm@381 150
rlm@381 151 Shigeki Goto, Hisao Nojima - Equilibrium analysis of the distribution
rlm@381 152 of information in human society
rlm@381 153
rlm@381 154 Raúl E. Valdés-Pérez - Machine discovery in chemistry: new results
rlm@381 155
rlm@381 156 Stephen W. Smoliar - Artificial life: Christopher G. Langton, ed.
rlm@381 157
rlm@381 158 Yoav Shoham, Moshe Tennenholtz - On social laws for artificial agent
rlm@381 159 societies: off-line design
rlm@381 160
rlm@381 161 Barbara Hayes-Roth - An architecture for adaptive intelligent systems
rlm@381 162
rlm@381 163 Bruce Randall Donald - On information invariants in robotics
rlm@381 164
rlm@381 165 Ian P. Gent, Toby Walsh - Easy problems are sometimes hard
rlm@381 166
rlm@381 167 Tad Hogg, Colin P. Williams - The hardest constraint problems: A
rlm@381 168 double phase transition
rlm@381 169
rlm@381 170 Yoram Moses, Yoav Shoham - Belief as defeasible knowledge
rlm@381 171
rlm@381 172 Donald Michie - Turing's test and conscious thought
rlm@381 173
rlm@381 174 John McDermott - R1 (“XCON”) at age 12: lessons from an elementary
rlm@381 175 school achiever
rlm@381 176
rlm@381 177 Takeo Kanade - From a real chair to a negative chair
rlm@381 178
rlm@381 179 Harry G. Barrow, J.M. Tenenbaum - Retrospective on “Interpreting line
rlm@381 180 drawings as three-dimensional surfaces”
rlm@381 181
rlm@381 182 Judea Pearl - Belief networks revisited
rlm@381 183
rlm@381 184 Glenn A. Kramer - A geometric constraint engine
rlm@381 185
rlm@381 186 Fausto Giunchiglia, Toby Walsh - A theory of abstraction
rlm@381 187
rlm@381 188 John L. Pollock - How to reason defeasibly
rlm@381 189
rlm@381 190 Aaron Sloman - The emperor's real mind: Review of Roger Penrose's the
rlm@381 191 emperor's new mind: Concerning computers, minds and the laws of
rlm@381 192 physics
rlm@381 193
rlm@381 194 Olivier Dordan - Mathematical problems arising in qualitative
rlm@381 195 simulation of a differential equation
rlm@381 196
rlm@381 197 Eric Saund - Putting knowledge into a visual shape representation
rlm@381 198
rlm@381 199 Michael Freund, Daniel Lehmann, Paul Morris - Rationality,
rlm@381 200 transitivity, and contraposition
rlm@381 201
rlm@381 202 Anthony S. Maida - Maintaining mental models of agents who have
rlm@381 203 existential misconceptions
rlm@381 204
rlm@381 205 Henry A. Kautz, Bart Selman - Hard problems for simple default logics
rlm@381 206
rlm@381 207 Mark J. Stefik, Stephen Smoliar - Four reviews of The Society of Mind
rlm@381 208 and a response
rlm@381 209
rlm@381 210 Michael G. Dyer - A society of ideas on cognition: Review of Marvin
rlm@381 211 Minsky's The Society of Mind
rlm@381 212
rlm@381 213 Matthew Ginsberg - The society of mind: Marvin Minsky
rlm@381 214
rlm@381 215 George N. Reeke Jr - The society of mind: Marvin Minsky
rlm@381 216
rlm@381 217 Stephen W. Smoliar - The society of mind: Marvin Minsky
rlm@381 218
rlm@381 219 Marvin Minsky - Society of mind: A response to four reviews
rlm@381 220
rlm@381 221 Stephen W. Smoliar - How to build a person: A prolegomenon: John
rlm@381 222 Pollock
rlm@381 223
rlm@381 224 David Makinson, Karl Schlechta - Floating conclusions and zombie
rlm@381 225 paths: Two deep difficulties in the “directly skeptical” approach to
rlm@381 226 defeasible inheritance nets
rlm@381 227
rlm@381 228 Donald A. Norman - Approaches to the study of intelligence
rlm@381 229
rlm@381 230 Rodney A. Brooks - Intelligence without representation
rlm@381 231
rlm@381 232 David Kirsh - Today the earwig, tomorrow man?
rlm@381 233
rlm@381 234 Douglas B. Lenat, Edward A. Feigenbaum - On the thresholds of
rlm@381 235 knowledge
rlm@381 236
rlm@381 237 Jordan B. Pollack - Recursive distributed representations
rlm@381 238
rlm@381 239 R. Bhaskar, Anil Nigam - Qualitative physics using dimensional
rlm@381 240 analysis
rlm@381 241
rlm@381 242 Don F. Beal - A generalised quiescence search algorithm
rlm@381 243
rlm@381 244 Kai-Fu Lee, Sanjoy Mahajan - The development of a world class Othello
rlm@381 245 program
rlm@381 246
rlm@381 247 Helmut Horacek - Reasoning with uncertainty in computer chess
rlm@381 248
rlm@381 249 Jeff Shrager - Induction: Process of inference, learning and
rlm@381 250 discovery: John H. Holland, Keith J. Holyoak, Richard E. Nisbett, and
rlm@381 251 Paul R. Thagard (MIT Press, Cambridge, MA, 1986); 355 pages
rlm@381 252
rlm@381 253 Daniel S. Weld - The psychology of everyday things: Donald A. Norman,
rlm@381 254 (Basic Books, New York, 1988); 257 pages, $19.95
rlm@381 255
rlm@381 256 John R. Anderson - A theory of the origins of human knowledge
rlm@381 257
rlm@381 258 G. Tesauro, T.J. Sejnowski - A parallel network that learns to play
rlm@381 259 backgammon
rlm@381 260
rlm@381 261 G. Priest - Reasoning about truth
rlm@381 262
rlm@381 263 Donald Perlis - Truth and meaning
rlm@381 264
rlm@381 265 Daniel S. Weld - Women, fire, and dangerous things: George Lakoff,
rlm@381 266 (University of Chicago Press, Chicago, IL, 1987); 614 pages, $29.95
rlm@381 267
rlm@381 268 Mark J. Stefik - On book reviews policy and process
rlm@381 269
rlm@381 270 Robert K. Lindsay - The science of the mind: Owen J. Flanagan, Jr.,
rlm@381 271 (MIT Press, Cambridge, MA, 1984); 290 pages
rlm@381 272
rlm@381 273 Sheila Rock - On machine intelligence: Donald Michie, 2nd ed. (Ellis
rlm@381 274 Horwood, Chichester, United Kingdom, 1986); 265 pages, £29.95
rlm@381 275
rlm@381 276 Stephen W. Smoliar - Epistemology and cognition: A.I. Goldman,
rlm@381 277 (Harvard University Press, Cambridge, MA, 1986); ix + 437 pages,
rlm@381 278 $27.50
rlm@381 279
rlm@381 280 David Elliot Shaw - On the range of applicability of an artificial
rlm@381 281 intelligence machine
rlm@381 282
rlm@381 283 Michael Gordon - Machine intelligence and related topics: An
rlm@381 284 information scientist's weekend book: Donald Michie, (Gordon and
rlm@381 285 Breach, New York, 1982); 328 pages, $57.75
rlm@381 286
rlm@381 287 Ryszard S. Michalski, Patrick H. Winston - Variable precision logic
rlm@381 288
rlm@381 289 Martin Herman, Takeo Kanade - Incremental reconstruction of 3D scenes
rlm@381 290 from multiple, complex images
rlm@381 291
rlm@381 292 vision : June 8–11, 1987, London, United Kingdom
rlm@381 293
rlm@381 294 André Vellino - Artificial intelligence: The very idea: J. Haugeland,
rlm@381 295 (MIT Press, Cambridge, MA, 1985); 287 pp.
rlm@381 296
rlm@381 297 Judea Pearl - Fusion, propagation, and structuring in belief networks
rlm@381 298
rlm@381 299 Daniel G. Bobrow - Scientific debate
rlm@381 300
rlm@381 301 Mark Stefik - The AI business: Commercial uses of artificial
rlm@381 302 intelligence: P.H. Winston and K.A. Prendergast, (MIT Press,
rlm@381 303 Cambridge, MA 1984); 324 pages, $15.95
rlm@381 304
rlm@381 305 Hans Berliner, Carl Ebeling - The SUPREM architecture: A new
rlm@381 306 intelligent paradigm
rlm@381 307
rlm@381 308 Donna Reese - Artificial intelligence: P.H. Winston, (Addison-Wesley,
rlm@381 309 Reading, MA, 2nd ed., 1984); 527 pages
rlm@381 310
rlm@381 311 Kenneth D. Forbus - Structure and interpretation of computer programs:
rlm@381 312 H. Abelson and G.J. Sussman with J. Sussman, (MIT, Cambridge, 1985);
rlm@381 313 503 pages
rlm@381 314
rlm@381 315 Chia-Hoang Lee, Azriel Rosenfeld - Improved methods of estimating
rlm@381 316 shape from shading using the light source coordinate system
rlm@381 317
rlm@381 318 Daniel G. Bobrow, Patrick J. Hayes - Artificial intelligence — Where
rlm@381 319 are we?
rlm@381 320
rlm@381 321 Barbara J. Grosz - Natural-language processing
rlm@381 322
rlm@381 323 Johan De Kleer - How circuits work
rlm@381 324
rlm@381 325 G.D. Ritchie, F.K. Hanna - am: A case study in AI methodology
rlm@381 326
rlm@381 327 Douglas B. Lenat, John Seely Brown - Why am and eurisko appear to work
rlm@381 328
rlm@381 329 Elaine Kant - On the efficient synthesis of efficient programs
rlm@381 330
rlm@381 331 Randall Davis, Reid G. Smith - Negotiation as a metaphor for
rlm@381 332 distributed problem solving
rlm@381 333
rlm@381 334 Patrick H. Winston - Learning new principles from precedents and
rlm@381 335 exercises
rlm@381 336
rlm@381 337 Paul S. Rosenbloom - A world-championship-level Othello program
rlm@381 338
rlm@381 339 Tomas Lozano-Perez - Robotics
rlm@381 340
rlm@381 341 Tom M. Mitchell - Generalization as search
rlm@381 342
rlm@381 343 Dana S. Nau - The last player theorem
rlm@381 344
rlm@381 345 Hans J. Berliner - Backgammon computer program beats world champion
rlm@381 346
rlm@381 347 Gerald Jay Sussman, Guy Lewis Steele Jr. - Constraints—A language for
rlm@381 348 expressing almost-hierarchical descriptions
rlm@381 349
rlm@381 350 Takeo Kanade - A theory of Origami world
rlm@381 351
rlm@381 352 Ria Follett - Synthesising recursive functions with side effects
rlm@381 353
rlm@381 354 John McCarthy - Circumscription—A form of non-monotonic reasoning
rlm@381 355
rlm@381 356 Michael A. Bauer - Programming by examples
rlm@381 357
rlm@381 358 Patrick H. Winston - Learning by creatifying transfer frames
rlm@381 359
rlm@381 360 Alan Bundy - Will it reach the top? Prediction in the mechanics world
rlm@381 361
rlm@381 362 Richard M. Stallman, Gerald J. Sussman - Forward reasoning and
rlm@381 363 dependency-directed backtracking in a system for computer-aided
rlm@381 364 circuit analysis
rlm@381 365
rlm@381 366 D. Marr - Artificial intelligence—A personal view
rlm@381 367
rlm@381 368 Berthold K.P. Horn - Understanding image intensities
rlm@381 369
rlm@381 370 F. Malloy Brown - Doing arithmetic without diagrams
rlm@381 371
rlm@381 372 Azriel Rosenfeld - The psychology of computer vision: Patrick Henry
rlm@381 373 Winston (ed.) McGraw-Hill, New York, 1975, vi+282 pages, $19.50
rlm@381 374
rlm@381 375 R.C.T. Lee - On machine intelligence: D. Michie. Halstead Press, a
rlm@381 376 division of John Wiley & Sons, 1974.
rlm@381 377
rlm@381 378 W.W. Bledsoe, Peter Bruell - A man-machine theorem-proving system
rlm@381 379
rlm@381 380 Gary G. Hendrix - Modeling simultaneous actions and continuous
rlm@381 381 processes
rlm@381 382
rlm@381 383 Yoshiaki Shirai - A context sensitive line finder for recognition of
rlm@381 384 polyhedra
rlm@381 385
rlm@381 386 Kenneth Mark Colby, Franklin Dennis Hilf, Sylvia Weber, Helena C
rlm@381 387 Kraemer - Turing-like indistinguishability tests for the validation of
rlm@381 388 a computer simulation of paranoid processes
rlm@381 389
rlm@381 390 Aaron Sloman - Interactions between philosophy and artificial
rlm@381 391 intelligence: The role of intuition and non-logical reasoning in
rlm@381 392 intelligence
rlm@381 393
rlm@381 394 * Story related
rlm@381 395
rlm@381 396 Charles B. Callaway, James C. Lester - Narrative prose generation
rlm@381 397
rlm@386 398 - Katja Markert, Udo Hahn :: Understanding metonymies in discourse
rlm@386 399 Metonymies are difficult enough to drive these people to use the
rlm@386 400 context of the sentences around the metonymy to interpret
rlm@386 401 it. They create a set of heuristics which interpret
rlm@386 402 metonomies. The first is obvious violations of sentence rules,
rlm@386 403 such as having a non-agent do something only an agent can do.
rlm@386 404
rlm@386 405 Another rule is that metonomyies should be more "apt", where it's
rlm@386 406 more likely for a T.V. Screen to refer to the T.V. than a small
rlm@386 407 button on the T.V., or a transistor.
rlm@386 408
rlm@386 409 Metonymies should be very difficult for current parsers to
rlm@386 410 understand, and are good examples, since they are short and
rlm@386 411 require context and common sense.
rlm@386 412
rlm@386 413 They have a dumb, ad-hoc "common sense database" that is
rlm@386 414 dissapointing. It contains subclasses and has-a relations.
rlm@386 415
rlm@386 416 References:
rlm@386 417 + D.A. Cruse, On the transitivity of the part-whole relation,
rlm@386 418 J. Linguistics 15 (1979) 29–38.
rlm@386 419 good quotes:
rlm@386 420 - We took the door off its hinges and went through it.
rlm@386 421 - The house has a handle.sources
rlm@386 422
rlm@381 423
rlm@381 424 Kathleen R. McKeown, Steven K. Feiner, Mukesh Dalal, Shih-Fu Chang -
rlm@381 425 Generating multimedia briefings: coordinating language and
rlm@381 426 illustration
rlm@381 427
rlm@381 428 Varol Akman - Formalizing common sense: Papers by John McCarthy:
rlm@381 429 V. Lifschitz, ed., (Ablex Publishing Corporation, Norwood, NJ, 1990);
rlm@381 430 vi+256 pages, hardback, ISBN 0-89391-535-1 (Library of Congress:
rlm@381 431 Q335.M38 1989)
rlm@381 432
rlm@381 433 Akira Shimaya - Interpreting non-3-D line drawings
rlm@381 434
rlm@381 435 Adam J. Grove - Naming and identity in epistemic logic part II: a
rlm@381 436 first-order logic for naming
rlm@381 437
rlm@381 438 Luc Lismont, Philippe Mongin - A non-minimal but very weak
rlm@381 439 axiomatization of common belief
rlm@381 440
rlm@381 441 on integration of natural language and vision processing
rlm@381 442
rlm@381 443 Russell Greiner - Learning by understanding analogies
rlm@381 444
rlm@381 445 * Review Articles
rlm@381 446
rlm@381 447 H.Jaap van den Herik, Jos W.H.M. Uiterwijk, Jack van Rijswijck - Games
rlm@381 448 solved: Now and in the future
rlm@381 449
rlm@381 450 Jonathan Schaeffer, H.Jaap van den Herik - Games, computers, and
rlm@381 451 artificial intelligence
rlm@381 452
rlm@381 453 Peter A. Flach - On the state of the art in machine learning: A
rlm@381 454 personal review
rlm@381 455
rlm@381 456 A.G. Cohn, D. Perlis - “Field Reviews”: A new style of review article
rlm@381 457 for Artificial Intelligence
rlm@381 458
rlm@381 459 James Delgrande, Arvind Gupta, Tim Van Allen - A comparison of
rlm@381 460 point-based approaches to qualitative temporal reasoning
rlm@381 461
rlm@381 462 Weixiong Zhang, Rina Dechter, Richard E. Korf - Heuristic search in
rlm@381 463 artificial intelligence
rlm@381 464
rlm@381 465 Karen Sparck Jones - Information retrieval and artificial intelligence
rlm@381 466
rlm@381 467 Wolfram Burgard, Armin B. Cremers, Dieter Fox, Dirk Hähnel, Gerhard
rlm@381 468 Lakemeyer, Dirk Schulz, Walter Steiner, Sebastian Thrun - Experiences
rlm@381 469 with an interactive museum tour-guide robot
rlm@381 470
rlm@381 471 Minoru Asada, Hiroaki Kitano, Itsuki Noda, Manuela Veloso - RoboCup:
rlm@381 472 Today and tomorrow—What we have learned
rlm@381 473
rlm@381 474 Margaret A. Boden - Creativity and artificial intelligence
rlm@381 475
rlm@381 476 Daniel G. Bobrow, J.Michael Brady - Artificial Intelligence 40 years
rlm@381 477 later
rlm@381 478
rlm@381 479 Fangzhen Lin, Hector J. Levesque - What robots can do: robot programs
rlm@381 480 and effective achievability
rlm@381 481
rlm@381 482 Melanie Mitchell - L.D. Davis, handbook of genetic algorithms
rlm@381 483
rlm@381 484 Russell Greiner, Adam J. Grove, Alexander Kogan - Knowing what doesn't
rlm@381 485 matter: exploiting the omission of irrelevant data
rlm@381 486
rlm@381 487 W. Whitney, S. Rana, J. Dzubera, K.E. Mathias - Evaluating
rlm@381 488 evolutionary algorithms
rlm@381 489
rlm@381 490 David S. Touretzky - Neural networks in artificial intelligence:
rlm@381 491 Matthew Zeidenberg
rlm@381 492
rlm@381 493 Mark J. Stefik, Stephen W. Smoliar - The commonsense reviews
rlm@381 494
rlm@381 495 Peter Szolovits, Stephen G. Pauker - Categorical and probabilistic
rlm@381 496 reasoning in medicine revisited
rlm@381 497
rlm@381 498 Daniel G. Bobrow - Artificial intelligence in perspective: a
rlm@381 499 retrospective on fifty volumes of the Artificial Intelligence Journal
rlm@381 500
rlm@381 501 David Kirsh - Foundations of AI: The big issues
rlm@381 502
rlm@381 503 Hector J. Levesque - All I know: A study in autoepistemic logic
rlm@381 504
rlm@381 505 J.T. Schwartz, M. Sharir - A survey of motion planning and related
rlm@381 506 geometric algorithms
rlm@381 507
rlm@381 508 Larry S. Davis, Azriel Rosenfeld - Cooperating processes for low-level
rlm@381 509 vision: A survey
rlm@381 510
rlm@381 511 Hans J. Berliner - A chronology of computer chess and its literature
rlm@381 512
rlm@381 513 John McCarthy - Artificial intelligence: a paper symposium: Professor
rlm@381 514 Sir James Lighthill, FRS. Artificial Intelligence: A General
rlm@381 515 Survey. In: Science Research Council, 1973
rlm@381 516 * Cortex related (sensory fusion / simulated worlds)
rlm@381 517
rlm@381 518 Alfonso Gerevini, Jochen Renz - Combining topological and size
rlm@381 519 information for spatial reasoning
rlm@381 520
rlm@381 521 John Slaney, Sylvie Thiébaux - Blocks World revisited
rlm@381 522
rlm@381 523 Wai K. Yeap, Margaret E. Jefferies - Computing a representation of the
rlm@381 524 local environment
rlm@381 525
rlm@381 526 R.P. Loui - On the origin of objects: B.C. Smith's MIT Press,
rlm@381 527 Cambridge, MA, 1996. $37.50 (cloth). $17.50 (paper). 440 pages. ISBN
rlm@381 528 0-262-69209-0
rlm@381 529
rlm@381 530 Tze Yun Leong - Multiple perspective dynamic decision making
rlm@381 531
rlm@381 532 Cristiano Castelfranchi - Modelling social action for AI agents
rlm@381 533
rlm@381 534 Luc Steels - The origins of syntax in visually grounded robotic agents
rlm@381 535
rlm@381 536 Sebastian Thrun - Learning metric-topological maps for indoor mobile
rlm@381 537 robot navigation
rlm@381 538
rlm@381 539 John Haugeland - Body and world: a review of What Computers Still
rlm@381 540 Can't Do: A critique of artificial reason (Hubert L. Dreyfus): (MIT
rlm@381 541 Press, Cambridge, MA, 1992); liii + 354 pages, $13.95
rlm@381 542
rlm@381 543 David J. Musliner, Edmund H. Durfee, Kang G. Shin - World modeling for
rlm@381 544 the dynamic construction of real-time control plans
rlm@381 545
rlm@381 546 Jozsef A. Toth - Reasoning agents in a dynamic world: The frame
rlm@381 547 problem: Kenneth M. Ford and Patrick J. Hayes, eds., (JAI Press,
rlm@381 548 Greenwich, CT, 1991); 290+xiv pages
rlm@381 549
rlm@381 550 Michael A. Arbib, Jim-Shih Liaw - Sensorimotor transformations in the
rlm@381 551 worlds of frogs and robots
rlm@381 552
rlm@381 553 Ingemar J. Cox, John J. Leonard - Modeling a dynamic environment using
rlm@381 554 a Bayesian multiple hypothesis approach
rlm@381 555
rlm@381 556 on integration of natural language and vision processing
rlm@381 557
rlm@381 558 Demetri Terzopoulos, Andrew Witkin, Michael Kass - Constraints on
rlm@381 559 deformable models:Recovering 3D shape and nonrigid motion
rlm@381 560
rlm@381 561 Bruce R. Donald - A search algorithm for motion planning with six
rlm@381 562 degrees of freedom
rlm@381 563
rlm@381 564 Yorick Wilks - Making preferences more active
rlm@381 565
rlm@381 566 * Vision Related
rlm@381 567
rlm@381 568 Azriel Rosenfeld - B. Jähne, H. Haussecker, and P. Geissler, eds.,
rlm@381 569 Handbook of Computer Vision and Applications. 1. Sensors and
rlm@381 570 Imaging. 2. Signal Processing and Pattern Recognition. 3. Systems and
rlm@381 571 Applications
rlm@381 572
rlm@381 573 Thomas F. Stahovich, Randall Davis, Howard Shrobe - Qualitative
rlm@381 574 rigid-body mechanics
rlm@381 575
rlm@381 576 Tzachi Dar, Leo Joskowicz, Ehud Rivlin - Understanding mechanical
rlm@381 577 motion: From images to behaviors
rlm@381 578
rlm@381 579 Minoru Asada, Eiji Uchibe, Koh Hosoda - Cooperative behavior
rlm@381 580 acquisition for mobile robots in dynamically changing real worlds via
rlm@381 581 vision-based reinforcement learning and development
rlm@381 582
rlm@381 583 Thomas F. Stahovich, Randall Davis, Howard Shrobe - Generating
rlm@381 584 multiple new designs from a sketch
rlm@381 585
rlm@381 586 Ernst D. Dickmanns - Vehicles capable of dynamic vision: a new breed
rlm@381 587 of technical beings?
rlm@381 588
rlm@381 589 Thomas G. Dietterich, Richard H. Lathrop, Tomás Lozano-Pérez - Solving
rlm@381 590 the multiple instance problem with axis-parallel rectangles
rlm@381 591
rlm@381 592 Rajesh P.N. Rao, Dana H. Ballard - An active vision architecture based
rlm@381 593 on iconic representations
rlm@381 594
rlm@381 595 John K. Tsotsos, Scan M. Culhane, Winky Yan Kei Wai, Yuzhong Lai, Neal
rlm@381 596 Davis, Fernando Nuflo - Modeling visual attention via selective tuning
rlm@381 597
rlm@381 598 Roger Mohr, Boubakeur Boufama, Pascal Brand - Understanding
rlm@381 599 positioning from multiple images
rlm@381 600
rlm@381 601 Andrew Zisserman, David Forsyth, Joseph Mundy, Charlie Rothwell, Jane
rlm@381 602 Liu, Nic Pillow - 3D object recognition using invariance
rlm@381 603
rlm@381 604 Naresh C. Gupta, Laveen N. Kanal - 3-D motion estimation from motion
rlm@381 605 field
rlm@381 606
rlm@381 607 Damian M. Lyons - Vision, instruction, and action: David Chapman, (MIT
rlm@381 608 Press Cambridge, MA, 1991); 295 pages, $35.00, (paperback)
rlm@381 609
rlm@381 610 Yoshinori Suganuma - Learning structures of visual patterns from
rlm@381 611 single instances
rlm@381 612
rlm@381 613 Dana H. Ballard - Animate vision
rlm@381 614
rlm@381 615 Raymond Reiter, Alan K. Mackworth - A logical framework for depiction
rlm@381 616 and image interpretation
rlm@381 617
rlm@381 618 Ellen Lowenfeld Walker, Martin Herman - Geometric reasoning for
rlm@381 619 constructing 3D scene descriptions from images
rlm@381 620
rlm@381 621 Michele Barry, David Cyrluk, Deepak Kapur, Joseph Mundy, Van-Duc
rlm@381 622 Nguyen - A multi-level geometric reasoning system for vision
rlm@381 623
rlm@381 624 Alex P. Pentland - Shading into texture
rlm@381 625
rlm@381 626 Brady - Parallelism in Vision
rlm@381 627
rlm@381 628 Jon A. Webb, J.K. Aggarwal - Structure from motion of rigid and
rlm@381 629 jointed objects
rlm@381 630
rlm@381 631 Michael Brady - Computer vision
rlm@381 632
rlm@381 633 Takeo Kanade - Recovery of the three-dimensional shape of an object
rlm@381 634 from a single view
rlm@381 635
rlm@381 636 Rodney A. Brooks - Symbolic reasoning among 3-D models and 2-D images
rlm@381 637
rlm@381 638 H.K. Nishihara - Intensity, visible-surface, and volumetric
rlm@381 639 representations
rlm@381 640
rlm@381 641 Thomas O. Binford - Inferring surfaces from images
rlm@381 642
rlm@381 643 Larry S. Davis, Azriel Rosenfeld - Cooperating processes for low-level
rlm@381 644 vision: A survey
rlm@381 645
rlm@384 646 - (1980) Berthold K.P. Horn, Brian G. Schunck - Determining optical
rlm@384 647 flow
rlm@384 648
rlm@384 649 Optical flow is an estimation of the movement of brightness
rlm@384 650 patterns. If the image is "smooth" then optical flow is also an
rlm@384 651 estimate of the movement of objects in the image (projected onto the
rlm@384 652 plane of the image). They get some fairly good results on some very
rlm@384 653 contrived examples. Important point is that calculating optical flow
rlm@384 654 involves a relaxation process where the velocities of regions of
rlm@384 655 constant brightness are inferred from the velocities of the edges of
rlm@384 656 those regions.
rlm@384 657
rlm@384 658 This paper is a lead up to Horn's book, Robot Vision.
rlm@384 659
rlm@384 660 Hexagonal sampling may be a good alternative to rectangular
rlm@384 661 sampling.
rlm@384 662
rlm@384 663 A reduced version of this algorithm is implemented in hardware in
rlm@384 664 optical mice to great effect.
rlm@384 665
rlm@384 666 + Hamming, R.W., Numerical Methods for Scientists and Engineers
rlm@384 667 (McGraw-Hill, New York, 1962).
rlm@384 668 + Limb, J.O. and Murphy, J.A., Estimating the velocity of moving
rlm@384 669 images in television signals, Computer Graphics and Image
rlm@384 670 Processing 4 (4) (1975) 311-327.
rlm@384 671 + Mersereau, R.M., The processing of hexagonally sampled
rlm@384 672 two-dimensional signals, Proc. of the IEEE 67 (6) (1979) 930-949.
rlm@384 673
rlm@384 674
rlm@384 675 - (1993) Berthold K.P. Horn, B.G. Schunck - “Determining optical flow”: a
rlm@384 676 retrospective
rlm@384 677
rlm@384 678 Very useful read where Horn criticies his previous paper.
rlm@384 679
rlm@384 680 - Whishes that he distinguished "optical flow" form "motion
rlm@384 681 field". "Optical flow" is an image property, whilc the "motion
rlm@384 682 field" is the movement of objects in 3D space. "Optical flow" is a
rlm@384 683 2D vector field; the "motion field" is 3D.
rlm@384 684 - Wished he made the limitations of his algorithm more clear.
rlm@384 685 - His original paper didn't concern itself with flow segmentation,
rlm@384 686 which is required to interpret real world images with objects and
rlm@384 687 a background.
rlm@384 688 - Thinks that the best thing about the original paper is that it
rlm@384 689 introduced variational calculus methods into computer vision.
rlm@384 690
rlm@384 691 References:
rlm@384 692
rlm@384 693 + R. Courant and D. Hilbert, Methods of Mathematical Physics
rlm@384 694 (Interscience, New York, 1937/1953).
rlm@384 695 + D. Mart, Vision (Freeman, San Francisco, CA, 1982).
rlm@384 696 + C.M. Thompson, Robust photo-topography by fusing
rlm@384 697 shape-from-shading and stereo,Ph.D. Thesis, Mechanical Engineering
rlm@384 698 Department, MIT, Cambridge, MA (1993).
rlm@384 699 + K. Ikeuchi and B.K.P. Horn, Numerical shape from shading and
rlm@384 700 occluding boundaries, Artif lntell. 17 (1981) 141-184.
rlm@381 701
rlm@381 702 Katsushi Ikeuchi, Berthold K.P. Horn - Numerical shape from shading
rlm@381 703 and occluding boundaries
rlm@381 704
rlm@381 705 Andrew P. Witkin - Recovering surface shape and orientation from
rlm@381 706 texture
rlm@381 707
rlm@381 708 Irwin Sobel - On calibrating computer controlled cameras for
rlm@381 709 perceiving 3-D scenes
rlm@381 710
rlm@381 711 P.M. Will, K.S. Pennington - Grid coding: A preprocessing technique
rlm@381 712 for robot and machine vision
rlm@381 713
rlm@381 714 M.B. Clowes - On seeing things
rlm@381 715
rlm@381 716 Claude R. Brice, Claude L. Fennema - Scene analysis using regions
rlm@383 717
rlm@383 718 * Cryo!
rlm@383 719
rlm@384 720 - (1999) Kenneth D. Forbus, Peter B. Whalley, John O. Everett, Leo
rlm@384 721 Ureel, Mike Brokowski, Julie Baher, Sven E. Kuehne - CyclePad: An
rlm@384 722 articulate virtual laboratory for engineering thermodynamics
rlm@384 723
rlm@384 724 Should learn about thermodynamics, and about "thermal cycles."
rlm@384 725 http://www.qrg.northwestern.edu/projects/NSF/cyclepad/cyclepad.htm
rlm@384 726
rlm@384 727 This system is more about expressing models and assumtions than
rlm@384 728 automatically generating them, and as such is similiar to our "math
rlm@384 729 language" idea.
rlm@384 730
rlm@384 731 It's like a simple circuit modeller, and similar to Dylan's idea of
rlm@384 732 an online circuit modeler.
rlm@384 733
rlm@384 734 #+begin_quote
rlm@384 735 We found that if CyclePad did not do the “obvious” propagation in
rlm@384 736 preference to interpolation, students trusted it less.
rlm@384 737 #+end_quote
rlm@384 738
rlm@384 739 It's too bad that the paper doesn't mention the shortcommings of the
rlm@384 740 system.
rlm@384 741
rlm@384 742 + J.O. Everett, Topological inference of teleology: Deriving
rlm@384 743 function from structure via evidential reasoning, Artificial
rlm@384 744 Intelligence 113 (1999) 149–202.
rlm@384 745 + P. Hayes, Naive physics 1: Ontology for liquids, in: J. Hobbs,
rlm@384 746 R. Moore (Eds.), Formal Theories of the Commonsense World, Ablex,
rlm@384 747 Norwood, NJ, 1985.
rlm@384 748 + P. Nayak, Automated modeling of physical systems, Ph.D. Thesis,
rlm@384 749 Computer Science Department, Stanford University, 1992.
rlm@384 750 + R.W. Haywood, Analysis of Engineering Cycles: Power, Refrigerating
rlm@384 751 and Gas Liquefaction Plant, Pergamon Press, 1985.
rlm@384 752 + R.M. Stallman, G.J. Sussman, Forward reasoning and
rlm@384 753 dependency-directed backtracking in a system for computer-aided
rlm@384 754 circuit analysis, Artificial Intelligence 9 (1977) 135–196.
rlm@384 755 + Dylan should read this, since it concerns his online circuit
rlm@384 756 analysis idea.
rlm@384 757
rlm@384 758