Linked bibliography for the SEP article "Connectionism" by Cameron Buckner and James Garson
This is an automatically generated and experimental page
If everything goes well, this page should display the bibliography of the aforementioned article as it appears in the Stanford Encyclopedia of Philosophy, but with links added to PhilPapers records and Google Scholar for your convenience. Some bibliographies are not going to be represented correctly or fully up to date. In general, bibliographies of recent works are going to be much better linked than bibliographies of primary literature and older works. Entries with PhilPapers records have links on their titles. A green link indicates that the item is available online at least partially.
This experiment has been authorized by the editors of the Stanford Encyclopedia of Philosophy. The original article and bibliography can be found here.
- Aizawa, Kenneth, 1994, “Representations without Rules, Connectionism and the Syntactic Argument”, Synthese, 101(3): 465–492. doi:10.1007/bf01063898 (Scholar)
- –––, 1997a, “Exhibiting versus Explaining Systematicity: A Reply to Hadley and Hayward”, Minds and Machines, 7(1): 39–55. doi:10.1023/a:1008203312152 (Scholar)
- –––, 1997b, “Explaining Systematicity”, Mind & Language, 12(2): 115–136. doi:10.1111/j.1468-0017.1997.tb00065.x (Scholar)
- –––, 2003, The Systematicity Arguments, Dordrecht: Kluwer. (Scholar)
- –––, 2014, “A Tough Time to be Talking
Systematicity”, in Calvo and Symons 2014: 77–101. (Scholar)
- Bechtel, William, 1987, “Connectionism and the Philosophy of Mind: An Overview”, The Southern Journal of Philosophy, 26(S1): 17–41. doi:10.1111/j.2041-6962.1988.tb00461.x (Scholar)
- –––, 1988, “Connectionism and Rules and Representation Systems: Are They Compatible?”, Philosophical Psychology, 1(1): 5–16. doi:10.1080/09515088808572922 (Scholar)
- Bechtel, William and Adele Abrahamsen, 1990, Connectionism and the Mind: An Introduction to Parallel Processing in Networks, Cambridge, MA: Blackwell. (Scholar)
- Bengio, Yoshua and Olivier Delalleau, 2011, “On the
Expressive Power of Deep Architectures”, in International
Conference on Algorithmic Learning Theory (ALT 2011), Jyrki
Kivinen, Csaba Szepesvári, Esko Ukkonen, and Thomas Zeugmann
(eds.) (Lecture Notes in Computer Science 6925), Berlin, Heidelberg:
Springer Berlin Heidelberg, 18–36.
doi:10.1007/978-3-642-24412-4_3 (Scholar)
- Bengio, Yoshua, Thomas Mesnard, Asja Fischer, Saizheng Zhang, and
Yuhuai Wu, 2017, “STDP-Compatible Approximation of
Backpropagation in an Energy-Based Model”, Neural
Computation, 29(3): 555–577. doi:10.1162/neco_a_00934 (Scholar)
- Bodén, Mikael and Lars Niklasson, 2000, “Semantic
Systematicity and Context in Connectionist Networks”,
Connection Science, 12(2): 111–142.
doi:10.1080/09540090050129754 (Scholar)
- Buckner, Cameron, 2018, “Empiricism without Magic: Transformational Abstraction in Deep Convolutional Neural Networks”, Synthese, 195(12): 5339–5372. doi:10.1007/s11229-018-01949-1 (Scholar)
- Butler, Keith, 1991, “Towards a Connectionist Cognitive Architecture”, Mind & Language, 6(3): 252–272. doi:10.1111/j.1468-0017.1991.tb00191.x (Scholar)
- Calvo Garzón, Francisco, 2003, “Connectionist Semantics and the Collateral Information Challenge”, Mind & Language, 18(1): 77–94. doi:10.1111/1468-0017.00215 (Scholar)
- Calvo, Paco and John Symons, 2014, The Architecture of
Cognition: Rethinking Fodor and Pylyshyn’s Systematicity
Challenge, Cambridge: MIT Press. (Scholar)
- Chalmers, David J., 1990, “Syntactic Transformations on Distributed Representations”, Connection Science, 2(1–2): 53–62. doi:10.1080/09540099008915662 (Scholar)
- –––, 1993, “Connectionism and Compositionality: Why Fodor and Pylyshyn Were Wrong”, Philosophical Psychology, 6(3): 305–319. doi:10.1080/09515089308573094 (Scholar)
- Chomsky, Noam, 1965, Aspects of the Theory of Syntax, Cambridge, MA: MIT Press. (Scholar)
- Christiansen, Morten H. and Nick Chater, 1994, “Generalization and Connectionist Language Learning”, Mind & Language, 9(3): 273–287. doi:10.1111/j.1468-0017.1994.tb00226.x (Scholar)
- –––, 1999a, “Toward a Connectionist Model of Recursion in Human Linguistic Performance”, Cognitive Science, 23(2): 157–205. doi:10.1207/s15516709cog2302_2 (Scholar)
- –––, 1999b, “Connectionist Natural Language Processing: The State of the Art”, Cognitive Science, 23(4): 417–437. doi:10.1207/s15516709cog2304_2 (Scholar)
- Churchland, Paul M., 1989, A Neurocomputational Perspective: The Nature of Mind and the Structure of Science, Cambridge, MA: MIT Press. (Scholar)
- –––, 1995, The Engine of Reason, the Seat of the Soul: A Philosophical Journey into the Brain, Cambridge, MA: MIT Press. (Scholar)
- –––, 1998, “Conceptual Similarity Across
Sensory and Neural Diversity: The Fodor/Lepore Challenge
Answered”, Journal of Philosophy, 95(1): 5–32.
doi:10.5840/jphil19989514 (Scholar)
- Clark, Andy, 1989, Microcognition: Philosophy, Cognitive Science, and Parallel Distributed Processing, (Explorations in Cognitive Science), Cambridge, MA: MIT Press. (Scholar)
- –––, 1990 [1995], “Connectionist
Minds”, Proceedings of the Aristotelian Society, 90:
83–102. Reprinted in MacDonald and MacDonald 1995:
339–356. doi:10.1093/aristotelian/90.1.83 (Scholar)
- –––, 1993, Associative Engines: Connectionism, Concepts, and Representational Change, Cambridge, MA: MIT Press. (Scholar)
- –––, 2013, “Whatever next? Predictive Brains, Situated Agents, and the Future of Cognitive Science”, Behavioral and Brain Sciences, 36(3): 181–204. doi:10.1017/s0140525x12000477 (Scholar)
- Clark, Andy and Rudi Lutz (eds.), 1992, Connectionism in
Context, London: Springer London.
doi:10.1007/978-1-4471-1923-4 (Scholar)
- Cotrell G.W. and S.L. Small, 1983, “A Connectionist Scheme
for Modeling Word Sense Disambiguation”, Cognition and Brain
Theory, 6(1): 89–120. (Scholar)
- Cummins, Robert, 1991, “The Role of Representation in Connectionist Explanations of Cognitive Capacities”, in Ramsey, Stich, and Rumelhart 1991: 91–114. (Scholar)
- –––, 1996, “Systematicity”:, Journal of Philosophy, 93(12): 591–614. doi:10.2307/2941118 (Scholar)
- Cummins, Robert and Georg Schwarz, 1991, “Connectionism, Computation, and Cognition”, in Horgan and Tienson 1991: 60–73. doi:10.1007/978-94-011-3524-5_3">10.1007/978-94-011-3524-5_3 (Scholar)
- Davies, Martin, 1989, “Connectionism, Modularity, and Tacit Knowledge”, The British Journal for the Philosophy of Science, 40(4): 541–555. doi:10.1093/bjps/40.4.541 (Scholar)
- –––, 1991, “Concepts, Connectionism and the Language of Thought”, in Ramsey, Stich, and Rumelhart 1991: 229–257. (Scholar)
- Dinsmore, John (ed.), 1992, The Symbolic and Connectionist Paradigms: Closing the Gap, Hillsdale, NJ: Erlbaum. (Scholar)
- Ehsan, Upol, Brent Harrison, Larry Chan, and Mark O. Riedl, 2018,
“Rationalization: A Neural Machine Translation Approach to
Generating Natural Language Explanations”, in Proceedings of
the 2018 AAAI/ACM Conference on AI, Ethics, and Society (AIES
’18), New Orleans, LA: ACM Press, 81–87.
doi:10.1145/3278721.3278736 (Scholar)
- Eliasmith, Chris, 2007, “How to Build a Brain: From Function to Implementation”, Synthese, 159(3): 373–388. doi:10.1007/s11229-007-9235-0 (Scholar)
- –––, 2013, How to Build a Brain: a Neural
Architecture for Biological Cognition, New York: Oxford
University Press. (Scholar)
- Elman, Jeffrey L., 1991, “Distributed Representations,
Simple Recurrent Networks, and Grammatical Structure”, in
Touretzky 1991: 91–122. doi:10.1007/978-1-4615-4008-3_5">10.1007/978-1-4615-4008-3_5 (Scholar)
- Elman, Jeffrey, Elizabeth Bates, Mark H. Johnson, Annette
Karmiloff-Smith,Domenico Parisi, and Kim Plunkett, 1996,
Rethinking Innateness: A Connectionist Perspective on
Development, Cambridge, MA: MIT Press. (Scholar)
- Elsayed, Gamaleldin F., Shreya Shankar, Brian Cheung, Nicolas
Papernot, Alexey Kurakin, Ian Goodfellow, and Jascha Sohl-Dickstein,
2018, “Adversarial Examples That Fool Both Computer Vision and
Time-Limited Humans”, in Proceedings of the 32Nd
International Conference on Neural Information Processing Systems,
(NIPS’18), 31: 3914–3924. (Scholar)
- Fodor, Jerry A., 1988, Psychosemantics: The Problem of Meaning in the Philosophy of Mind, Cambridge, MA: MIT Press. (Scholar)
- –––, 1997, “Connectionism and the Problem of Systematicity (Continued): Why Smolensky’s Solution Still Doesn’t Work”, Cognition, 62(1): 109–119. doi:10.1016/s0010-0277(96)00780-9 (Scholar)
- Fodor, Jerry and Ernest Lepore, 1992, Holism: A Shopper’s Guide, Cambridge: Blackwell. (Scholar)
- Fodor, Jerry and Ernie Lepore, 1999, “All at Sea in Semantic Space: Churchland on Meaning Similarity”, Journal of Philosophy, 96(8): 381–403. doi:10.5840/jphil199996818 (Scholar)
- Fodor, Jerry and Brian P. McLaughlin, 1990, “Connectionism and the Problem of Systematicity: Why Smolensky’s Solution Doesn’t Work”, Cognition, 35(2): 183–204. doi:10.1016/0010-0277(90)90014-b (Scholar)
- Fodor, Jerry A. and Zenon W. Pylyshyn, 1988, “Connectionism and Cognitive Architecture: A Critical Analysis”, Cognition, 28(1–2): 3–71. doi:10.1016/0010-0277(88)90031-5 (Scholar)
- Friston, Karl, 2005, “A Theory of Cortical Responses”,
Philosophical Transactions of the Royal Society B: Biological
Sciences, 360(1456): 815–836.
doi:10.1098/rstb.2005.1622 (Scholar)
- Friston, Karl J. and Klaas E. Stephan, 2007, “Free-Energy and the Brain”, Synthese, 159(3): 417–458. doi:10.1007/s11229-007-9237-y (Scholar)
- Fukushima, Kunihiko, 1980, “Neocognitron: A Self-Organizing
Neural Network Model for a Mechanism of Pattern Recognition Unaffected
by Shift in Position”, Biological Cybernetics, 36(4):
193–202. doi:10.1007/bf00344251 (Scholar)
- Garfield, Jay L., 1997, “Mentalese Not Spoken Here: Computation, Cognition and Causation”, Philosophical Psychology, 10(4): 413–435. doi:10.1080/09515089708573231 (Scholar)
- Garson, James W., 1991, “What Connectionists Cannot Do: The Threat to Classical AI”, in Horgan and Tienson 1991: 113–142. doi:10.1007/978-94-011-3524-5_6 (Scholar)
- –––, 1994, “Cognition without Classical Architecture”, Synthese, 100(2): 291–305. doi:10.1007/bf01063812 (Scholar)
- –––, 1997, “Syntax in a Dynamic Brain”, Synthese, 110(3): 343–355. (Scholar)
- Goodfellow, Ian, Yoshua Bengio, and Aaron Courville, 2016,
Deep Learning, Cambridge, MA: MIT Press. (Scholar)
- Goodfellow, Ian J., Jonathon Shlens, and Christian Szegedy, 2015,
“Explaining and Harnessing Adversarial Examples.”, in
3rd International Conference on Learning Representations, ICLR
2015, San Diego, CA, May 7–9, 2015,
available online. (Scholar)
- Goodfellow, Ian J., Jean Pouget-Abadie, Mehdi Mirza, Bing Xu,
David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio,
2014, “Generative Adversarial Nets”, in Proceedings of
the 27th International Conference on Neural Information Processing
Systems, (NIPS’14), Cambridge, MA: MIT Press, 2:
2672–2680. (Scholar)
- Goodman, Bryce and Seth Flaxman, 2017, “European Union
Regulations on Algorithmic Decision-Making and a ‘Right to
Explanation’”, AI Magazine, 38(3): 50–57.
doi:10.1609/aimag.v38i3.2741 (Scholar)
- Goodman, Nelson, 1955, Fact, Fiction, and Forecast, Cambridge, MA: Harvard University Press. (Scholar)
- Grush, Rick, 2004, “The Emulation Theory of Representation: Motor Control, Imagery, and Perception”, Behavioral and Brain Sciences, 27(3): 377–396. doi:10.1017/s0140525x04000093 (Scholar)
- Guarini, Marcello, 2001, “A Defence of Connectionism Against the ‘Syntactic’ Argument”, Synthese, 128(3): 287–317. doi:10.1023/a:1011905917986 (Scholar)
- Hadley, Robert F., 1994a, “Systematicity in Connectionist Language Learning”, Mind & Language, 9(3): 247–272. doi:10.1111/j.1468-0017.1994.tb00225.x (Scholar)
- –––, 1994b, “Systematicity Revisited: Reply to Christiansen and Chater and Niklasson and van Gelder”, Mind & Language, 9(4): 431–444. doi:10.1111/j.1468-0017.1994.tb00317.x (Scholar)
- –––, 1997a, “Explaining Systematicity: A Reply to Kenneth Aizawa”, Minds and Machines, 7(4): 571–579. doi:10.1023/a:1008252322227 (Scholar)
- –––, 1997b, “Cognition, Systematicity and Nomic Necessity”, Mind & Language, 12(2): 137–153. doi:10.1111/j.1468-0017.1997.tb00066.x (Scholar)
- –––, 2004, “On The Proper Treatment of Semantic Systematicity”, Minds and Machines, 14(2): 145–172. doi:10.1023/b:mind.0000021693.67203.46 (Scholar)
- Hadley, Robert F. and Michael B. Hayward, 1997, “Strong Semantic Systematicity from Hebbian Connectionist Learning”, Minds and Machines, 7(1): 1–37. doi:10.1023/a:1008252408222 (Scholar)
- Hanson, Stephen J. and Judy Kegl, 1987, “PARSNIP: A
Connectionist Network that Learns Natural Language Grammar from
Exposure to Natural Language Sentences”, Ninth Annual
Conference of the Cognitive Science Society, Hillsdale, NJ:
Erlbaum, pp. 106–119. (Scholar)
- Harman, Gilbert and Sanjeev Kulkarni, 2007, Reliable Reasoning: Induction and Statistical Learning Theory, Cambridge MA: MIT Press. (Scholar)
- Hatfield, Gary, 1991a, “Representation in Perception and Cognition: Connectionist Affordances”, in Ramsey, Stich, and Rumelhart 1991: 163–195. (Scholar)
- –––, 1991b, “Representation and Rule-Instantiation in Connectionist Systems”, in Horgan and Tienson 1991: 90–112. doi:10.1007/978-94-011-3524-5_5 (Scholar)
- Hawthorne, John, 1989, “On the Compatibility of Connectionist and Classical Models”, Philosophical Psychology, 2(1): 5–15. doi:10.1080/09515088908572956 (Scholar)
- Haybron, Daniel M., 2000, “The Causal and Explanatory Role of Information Stored in Connectionist Networks”, Minds and Machines, 10(3): 361–380. doi:10.1023/a:1026545231550 (Scholar)
- Hinton, Geoffrey E., 1990 [1991], “Mapping Part-Whole
Hierarchies into Connectionist Networks”, Artificial
Intelligence, 46(1–2): 47–75. Reprinted in Hinton
1991: 47–76. doi:10.1016/0004-3702(90)90004-J (Scholar)
- ––– (ed.), 1991, Connectionist Symbol
Processing, Cambridge, MA: MIT Press. (Scholar)
- –––, 1992, “How Neural Networks Learn from
Experience”, Scientific American, 267(3):
145–151. (Scholar)
- –––, 2010, “Learning to Represent Visual
Input”, Philosophical Transactions of the Royal Society B:
Biological Sciences, 365(1537): 177–184.
doi:10.1098/rstb.2009.0200 (Scholar)
- Hinton, Geoffrey E., James L. McClelland, and David E. Rumelhart,
1986, “Distributed Representations”, Rumelhart,
McClelland, and the PDP group 1986: chapter 3. (Scholar)
- Hohwy, Jakob, 2012, “Attention and Conscious Perception in
the Hypothesis Testing Brain”, Frontiers in Psychology,
3(96): 1–14. doi:10.3389/fpsyg.2012.00096 (Scholar)
- Hong, Ha, Daniel L K Yamins, Najib J Majaj, and James J DiCarlo,
2016, “Explicit Information for Category-Orthogonal Object
Properties Increases along the Ventral Stream”, Nature
Neuroscience, 19(4): 613–622. doi:10.1038/nn.4247 (Scholar)
- Horgan, Terence E. and John Tienson, 1989, “Representations without Rules”, Philosophical Topics, 17(1): 147–174. (Scholar)
- –––, 1990, “Soft Laws”, Midwest Studies In Philosophy, 15: 256–279. doi:10.1111/j.1475-4975.1990.tb00217.x (Scholar)
- ––– (eds.), 1991, Connectionism and the Philosophy of Mind, Dordrecht: Kluwer. doi:10.1007/978-94-011-3524-5 (Scholar)
- –––, 1996, Connectionism and the Philosophy of Psychology, Cambridge, MA: MIT Press. (Scholar)
- Hosoya, Toshihiko, Stephen A. Baccus, and Markus Meister, 2005,
“Dynamic Predictive Coding by the Retina”,
Nature, 436(7047): 71–77. doi:10.1038/nature03689 (Scholar)
- Huang, Yanping and Rajesh P. N. Rao, 2011, “Predictive
Coding”, Wiley Interdisciplinary Reviews: Cognitive
Science, 2(5): 580–593. doi:10.1002/wcs.142 (Scholar)
- Hubel, David H. and Torsten N. Wiesel, 1965, “Receptive
Fields and Functional Architecture in Two Nonstriate Visual Areas (18
and 19) of the Cat”, Journal of Neurophysiology, 28(2):
229–289. doi:10.1152/jn.1965.28.2.229 (Scholar)
- Jansen, Peter A. and Scott Watter, 2012, “Strong
Systematicity through Sensorimotor Conceptual Grounding: An
Unsupervised, Developmental Approach to Connectionist Sentence
Processing”, Connection Science, 24(1): 25–55.
doi:10.1080/09540091.2012.664121 (Scholar)
- Johnson, Kent, 2004, “On the Systematicity of Language and Thought”:, Journal of Philosophy, 101(3): 111–139. doi:10.5840/jphil2004101321 (Scholar)
- Jones, Matt and Bradley C. Love, 2011, “Bayesian Fundamentalism or Enlightenment? On the Explanatory Status and Theoretical Contributions of Bayesian Models of Cognition”, Behavioral and Brain Sciences, 34(4): 169–188. doi:10.1017/s0140525x10003134 (Scholar)
- Khaligh-Razavi, Seyed-Mahdi and Nikolaus Kriegeskorte, 2014,
“Deep Supervised, but Not Unsupervised, Models May Explain IT
Cortical Representation”, PLoS Computational Biology,
10(11): e1003915. doi:10.1371/journal.pcbi.1003915 (Scholar)
- Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton, 2012,
“Imagenet Classification with Deep Convolutional Neural
Networks”, Advances in Neural Information Processing
Systems, 25: 1097–1105. (Scholar)
- Kubilius, Jonas, Stefania Bracci, and Hans P. Op de Beeck, 2016,
“Deep Neural Networks as a Computational Model for Human Shape
Sensitivity”, PLOS Computational Biology, 12(4):
e1004896. doi:10.1371/journal.pcbi.1004896 (Scholar)
- Laakso, Aarre and Garrison Cottrell, 2000, “Content and Cluster Analysis: Assessing Representational Similarity in Neural Systems”, Philosophical Psychology, 13(1): 47–76. doi:10.1080/09515080050002726 (Scholar)
- Lake, Brenden M., Ruslan Salakhutdinov, and Joshua B. Tenenbaum,
2015, “Human-Level Concept Learning through Probabilistic
Program Induction”, Science, 350(6266):
1332–1338. doi:10.1126/science.aab3050 (Scholar)
- Lake, Brenden M., Wojciech Zaremba, Rob Fergus, and Todd M.
Gureckis, 2015, “Deep Neural Networks Predict Category
Typicality Ratings for Images”, Proceedings of the 37th
Annual Cognitive Science Society, Pasadena, CA, 22–25 July
2015, available online. (Scholar)
- Lillicrap, Timothy P., Daniel Cownden, Douglas B. Tweed, and Colin
J. Akerman, 2016, “Random Synaptic Feedback Weights Support
Error Backpropagation for Deep Learning”, Nature
Communications, 7(1): 13276. doi:10.1038/ncomms13276 (Scholar)
- Loula, João, Marco Baroni, and Brenden Lake, 2018,
“Rearranging the Familiar: Testing Compositional Generalization
in Recurrent Networks”, in Proceedings of the 2018 EMNLP
Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for
NLP, Brussels, Belgium: Association for Computational
Linguistics, 108–114. doi:10.18653/v1/w18-5413 (Scholar)
- MacDonald, Cynthia and Graham MacDonald (eds), 1995,
Connectionism, (Debates on Psychological Explanation, 2),
Oxford: Blackwell. (Scholar)
- Matthews, Robert J., 1997, “Can Connectionists Explain Systematicity?”, Mind & Language, 12(2): 154–177. doi:10.1111/j.1468-0017.1997.tb00067.x (Scholar)
- Marcus, Gary F., 1998, “Rethinking Eliminative
Connectionism”, Cognitive Psychology, 37(3):
243–282. doi:10.1006/cogp.1998.0694 (Scholar)
- –––, 2001, The Algebraic Mind: Integrating Connectionism and Cognitive Science, Cambridge, MA: MIT Press. (Scholar)
- McClelland, James L and Jeffrey L Elman, 1986, “The TRACE
Model of Speech Perception”, Cognitive Psychology,
18(1): 1–86. doi:10.1016/0010-0285(86)90015-0 (Scholar)
- McClelland, James L., David E. Rumelhart, and the PDP Research
Group (ed.), 1986, Parallel Distributed Processing, Volume II:
Explorations in the Microstructure of Cognition: Psychological and
Biological Models, Cambridge, MA: MIT Press. (Scholar)
- McLaughlin, Brian P., 1993, “The Connectionism/Classicism Battle to Win Souls”, Philosophical Studies, 71(2): 163–190. doi:10.1007/bf00989855 (Scholar)
- Miikkulainen, Risto, 1993, Subsymbolic Natural Language
Processing: An Integrated Model of Scripts, Lexicon, and Memory,
Cambridge, MA: MIT Press. (Scholar)
- Miikkulainen, Risto and Michael G. Dyer, 1991, “Natural Language Processing With Modular Pdp Networks and Distributed Lexicon”, Cognitive Science, 15(3): 343–399. doi:10.1207/s15516709cog1503_2 (Scholar)
- Miracchi, Lisa, 2019, “A Competence Framework for Artificial Intelligence Research”, Philosophical Psychology, 32(5): 588–633. doi:10.1080/09515089.2019.1607692 (Scholar)
- Montavon, Grégoire, Wojciech Samek, and Klaus-Robert
Müller, 2018, “Methods for Interpreting and Understanding
Deep Neural Networks”, Digital Signal Processing, 73:
1–15. doi:10.1016/j.dsp.2017.10.011 (Scholar)
- Montúfar, Guido, Razvan Pascanu, Kyunghyun Cho, and Yoshua
Bengio, 2014, “On the Number of Linear Regions of Deep Neural
Networks”, in Proceedings of the 27th International
Conference on Neural Information Processing Systems
(NIPS’14), Cambridge, MA: MIT Press, 2: 2924–2932.
(Scholar)
- Morris, William C., Garrison W. Cottrell, and Jeffrey Elman, 2000,
“A Connectionist Simulation of the Empirical Acquisition of
Grammatical Relations”, in Wermter and Sun 2000:
1778:175–193. doi:10.1007/10719871_12">10.1007/10719871_12 (Scholar)
- Nguyen, Anh, Jason Yosinski, Jeff Clune, 2015, “Deep Neural
Networks Are Easily Fooled: High Confidence Predictions for
Unrecognizable Images”, Proceedings of the 28th IEEE
Conference on Computer Vision and Pattern Recognition (CVPR
2015), 427–436,
available online. (Scholar)
- Niklasson, Lars F. and Tim van Gelder, 1994, “On Being Systematically Connectionist”, Mind & Language, 9(3): 288–302. doi:10.1111/j.1468-0017.1994.tb00227.x (Scholar)
- O’Reilly, Randall C., 1996, “Biologically Plausible
Error-Driven Learning Using Local Activation Differences: The
Generalized Recirculation Algorithm”, Neural
Computation, 8(5): 895–938.
doi:10.1162/neco.1996.8.5.895 (Scholar)
- Phillips, Steven, 2002, “Does Classicism Explain Universality?”, Minds and Machines, 12(3): 423–434. doi:10.1023/a:1016160512967 (Scholar)
- Pinker, Steven and Jacques Mehler (eds.), 1988, Connections
and Symbols, Cambridge, MA: MIT Press. (Scholar)
- Pinker, Steven and Alan Prince, 1988, “On Language and Connectionism: Analysis of a Parallel Distributed Processing Model of Language Acquisition”, Cognition, 28(1–2): 73–193. doi:10.1016/0010-0277(88)90032-7 (Scholar)
- Pollack, Jordan B., 1989, “Implications of Recursive
Distributed Representations”, in Touretzky 1989: 527–535,
available online. (Scholar)
- –––, 1991, “Induction of Dynamical
Recognizers”, in Touretzky 1991: 123–148.
doi:10.1007/978-1-4615-4008-3_6 (Scholar)
- Pollack, Jordan B., 1990 [1991], “Recursive Distributed
Representations”, Artificial Intelligence,
46(1–2): 77–105. Reprinted in Hinton 1991: 77–106.
doi:10.1016/0004-3702(90)90005-K (Scholar)
- Port, Robert F., 1990, “Representation and Recognition of
Temporal Patterns”, Connection Science, 2(1–2):
151–176. doi:10.1080/09540099008915667 (Scholar)
- Port, Robert F. and Timothy van Gelder, 1991, “Representing
Aspects of Language”, Proceedings of the Thirteenth Annual
Conference of the Cognitive Science Society, Hillsdale, N.J.:
Erlbaum, 487–492,
available online. (Scholar)
- Quine, W. V., 1969, “Natural Kinds”, in Essays in Honor of Carl G. Hempel, Nicholas Rescher (ed.), Dordrecht: Springer Netherlands, 5–23. doi:10.1007/978-94-017-1466-2_2 (Scholar)
- Raghu, Maithra, Ben Poole, Jon Kleinberg, Surya Ganguli, and
Jascha Sohl-Dickstein, 2017, “On the Expressive Power of Deep
Neural Networks”, in Proceedings of the 34th International
Conference on Machine Learning, 70: 2847–2854,
available online. (Scholar)
- Ramsey, William, 1997, “Do Connectionist Representations Earn Their Explanatory Keep?”, Mind & Language, 12(1): 34–66. doi:10.1111/j.1468-0017.1997.tb00061.x (Scholar)
- Ramsey, William, Stephen P. Stich, and Joseph Garon, 1991,
“Connectionism, Eliminativism, and the Future of Folk
Psychology”, in Ramsey, Stich, and Rumelhart 1991:
199–228. (Scholar)
- Ramsey, William, Stephen P. Stich, and David E. Rumelhart, 1991,
Philosophy and Connectionist Theory, Hillsdale, N.J.:
Erlbaum. (Scholar)
- Rao, Rajesh P. N. and Dana H. Ballard, 1999, “Predictive
Coding in the Visual Cortex: A Functional Interpretation of Some
Extra-Classical Receptive-Field Effects”, Nature
Neuroscience, 2(1): 79–87. doi:10.1038/4580 (Scholar)
- Rohde, Douglas L. T. and David C. Plaut, 2003,
“Connectionist Models of Language Processing”,
Cognitive Studies (Japan), 10(1): 10–28.
doi:10.11225/jcss.10.10 (Scholar)
- Roth, Martin, 2005, “Program Execution in Connectionist Networks”, Mind & Language, 20(4): 448–467. doi:10.1111/j.0268-1064.2005.00295.x (Scholar)
- Rumelhart, David E. and James L. McClelland, 1986, “On
Learning the Past Tenses of English Verbs”, in McClelland,
Rumelhart, and the PDP group 1986: 216–271. (Scholar)
- Rumelhart, David E., James L. McClelland, and the PDP Research
Group (eds), 1986, Parallel Distributed Processing, Volume 1:
Explorations in the Microstructure of Cognition: Foundations,
Cambridge, MA: MIT Press. (Scholar)
- Sadler, Matthew and Natasha Regan, 2019, Game Changer:
AlphaZero’s Groundbreaking Chess Strategies and the Promise of
AI, Alkmaar: New in Chess. (Scholar)
- Schmidhuber, Jürgen, 2015, “Deep Learning in Neural
Networks: An Overview”, Neural Networks, 61:
85–117. doi:10.1016/j.neunet.2014.09.003 (Scholar)
- Schwarz, Georg, 1992, “Connectionism, Processing,
Memory”, Connection Science, 4(3–4):
207–226. doi:10.1080/09540099208946616 (Scholar)
- Sejnowski, Terrence J. and Charles R. Rosenberg, 1987,
“Parallel Networks that Learn to Pronounce English Text”,
Complex Systems, 1(1): 145–168,
available online. (Scholar)
- Servan-Schreiber, David, Axel Cleeremans, and James L. McClelland,
1991, “Graded State Machines: The Representation of Temporal
Contingencies in Simple Recurrent Networks”, in Touretzky 1991:
57–89. doi:10.1007/978-1-4615-4008-3_4 (Scholar)
- Shastri, Lokendra and Venkat Ajjanagadde, 1993, “From Simple Associations to Systematic Reasoning: A Connectionist Representation of Rules, Variables and Dynamic Bindings Using Temporal Synchrony”, Behavioral and Brain Sciences, 16(3): 417–451. doi:10.1017/s0140525x00030910 (Scholar)
- Shea, Nicholas, 2007, “Content and Its Vehicles in Connectionist Systems”, Mind & Language, 22(3): 246–269. doi:10.1111/j.1468-0017.2007.00308.x (Scholar)
- Shevlin, Henry and Marta Halina, 2019, “Apply Rich
Psychological Terms in AI with Care”, Nature Machine
Intelligence, 1(4): 165–167.
doi:10.1038/s42256-019-0039-y (Scholar)
- Shultz, Thomas R. and Alan C. Bale, 2001, “Neural Network
Simulation of Infant Familiarization to Artificial Sentences”,
Infancy, 2(4): 501–536. (Scholar)
- –––, 2006, “Neural Networks Discover a Near-Identity Relation to Distinguish Simple Syntactic Forms”, Minds and Machines, 16(2): 107–139. doi:10.1007/s11023-006-9029-z (Scholar)
- Silver, David, Thomas Hubert, Julian Schrittwieser, Ioannis
Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, et al., 2018,
“A General Reinforcement Learning Algorithm That Masters Chess,
Shogi, and Go through Self-Play”, Science, 362(6419):
1140–1144. doi:10.1126/science.aar6404 (Scholar)
- Smolensky, Paul, 1987, “The Constituent Structure of Connectionist Mental States: A Reply to Fodor and Pylyshyn”, The Southern Journal of Philosophy, 26(S1): 137–161. doi:10.1111/j.2041-6962.1988.tb00470.x (Scholar)
- –––, 1988, “On the Proper Treatment of Connectionism”, Behavioral and Brain Sciences, 11(1): 1–23. doi:10.1017/s0140525x00052432 (Scholar)
- –––, 1990 [1991], “Tensor Product Variable
Binding and the Representation of Symbolic Structures in Connectionist
Systems”, Artificial Intelligence, 46(1–2):
159–216. Reprinted in Hinton 1991: 159–216.
doi:10.1016/0004-3702(90)90007-M (Scholar)
- –––, 1995, “Constituent Structure and
Explanation in an Integrated Connectionist/Symbolic Cognitive
Architecture”, in MacDonald and MacDonald 1995: . (Scholar)
- St. John, Mark F. and James L. McClelland, 1990 [1991],
“Learning and Applying Contextual Constraints in Sentence
Comprehension”, Artificial Intelligence, 46(1–2):
217–257. Reprinted in Hinton 1991: 217–257
doi:10.1016/0004-3702(90)90008-N (Scholar)
- Tomberlin, James E. (ed.), 1995, Philosophical Perspectives 9:
AI, Connectionism and Philosophical Psychology, Atascadero:
Ridgeview Press. (Scholar)
- Touretzky, David S. (ed.), 1989, Advances in Neural
Information Processing Systems I, San Mateo, CA: Kaufmann,
available online. (Scholar)
- ––– (ed.), 1990, Advances in Neural
Information Processing Systems II, San Mateo, CA: Kaufmann. (Scholar)
- ––– (ed.), 1991, Connectionist Approaches to
Language Learning, Boston, MA: Springer US.
doi:10.1007/978-1-4615-4008-3 (Scholar)
- Touretzky, David S., Geoffrey E. Hinton, and Terrence Joseph
Sejnowski (eds), 1988, Proceedings of the 1988 Connectionist
Models Summer School, San Mateo, CA: Kaufmann. (Scholar)
- Van Gelder, Tim, 1990, “Compositionality: A Connectionist
Variation on a Classical Theme”, Cognitive Science,
14(3): 355–384. doi:10.1016/0364-0213(90)90017-q (Scholar)
- –––, 1991, “What is the ‘D’ in
PDP?” in Ramsey, Stich, and Rumelhart 1991: 33–59. (Scholar)
- Van Gelder, Timothy and Robert Port, 1993, “Beyond Symbolic:
Prolegomena to a Kama-Sutra of Compositionality”, in Vasant G
Honavar, Leonard Uhr (eds.), Symbol Processing and Connectionist
Models in AI and Cognition: Steps Towards Integration, Boston:
Academic Press. (Scholar)
- Vilcu, Marius and Robert F. Hadley, 2005, “Two Apparent ‘Counterexamples’ to Marcus: A Closer Look”, Minds and Machines, 15(3–4): 359–382. doi:10.1007/s11023-005-9000-4 (Scholar)
- Von Eckardt, Barbara, 2003, “The Explanatory Need for Mental Representations in Cognitive Science”, Mind & Language, 18(4): 427–439. doi:10.1111/1468-0017.00235 (Scholar)
- –––, 2005, “Connectionism and the Propositional Attitudes”, in Christina Erneling and David Martel Johnson (eds.), The Mind as a Scientific Object: Between Brain and Culture, New York: Oxford University Press. (Scholar)
- Waltz, David L. and Jordan B. Pollack, 1985, “Massively Parallel Parsing: A Strongly Interactive Model of Natural Language Interpretation*”, Cognitive Science, 9(1): 51–74. doi:10.1207/s15516709cog0901_4 (Scholar)
- Wermter, Stefan and Ron Sun (eds.), 2000, Hybrid Neural
Systems, (Lecture Notes in Computer Science 1778), Berlin,
Heidelberg: Springer Berlin Heidelberg. doi:10.1007/10719871 (Scholar)
- Yamins, Daniel L. K. and James J. DiCarlo, 2016, “Using
Goal-Driven Deep Learning Models to Understand Sensory Cortex”,
Nature Neuroscience, 19(3): 356–365.
doi:10.1038/nn.4244 (Scholar)
- Yosinski, Jason, Jeff Clune, Anh Nguyen, Thomas Fuchs, and Hod
Lipson, 2015, “Understanding Neural Networks Through Deep
Visualization”, Deep Learning Workshop, 31st International
Conference on Machine Learning, Lille, France,
available online. (Scholar)
- Zhou, Zhenglong and Chaz Firestone, 2019, “Humans Can
Decipher Adversarial Images”, Nature Communications,
10(1): 1334. doi:10.1038/s41467-019-08931-6 (Scholar)