What is thought? From its inception, Cognitive Science explored two kinds of answers:

- discrete symbol manipulation
- parallel analogical processes

The first kind of answer is rooted in the study of logic as the foundation of (mathematical) reasoning, which gave rise to formal systems, formal grammars and automata theory. These theories were applied in Cognitive Science to the modeling of common-sense reasoning (symbolic AI) and language (formal & computational linguisics).

The second kind of answer is rooted into the study of the brain and of the property of large networks of simple analogical devices. It gave rise to the field of computational neuroscience which is applied to the modeling of many cognitive functions (perception, memory, action, etc) as well as of functional neurophysiological data.

These two lines of research gave rise in the 80s to a large scale confrontation, largely focussed on the study of language. The symbolic versus connectionist debate was ignited by the publication of two landmark volumes (Rumelhart & McClelland, 1986; McClelland & Rumelhard, 1986). Paralleled Distributed Processing was described as a new theory of cognition challenging the idea of symbolic computation that was at the center of debate in theoretical discussions about the mind. The response took the shape of a special cognition issue Connections and Symbols (Pinker & Mehler, 1988), as well as a wealth of empirical and theoretical results that have profoundly modified the field of Cognitive Science.

In this course, we will review some of the theoretical background to understand this debate, and discuss some of positions and arguments.

Topics covered:

- Formal systems
- Formal languages (regular, algrebraic, recursively enumerable)
- Chomsky's hierarchy (finite state, push down, Turing)
- McCullogh & Pitt's neurons
- Delta Rule, (multilayered) perceptrons, and backpropagation
- Hebb's rule, Hopfield's nets
- Applications in cognitive science

__PDF of session 1__

__Reference books__

- Rumelhart, D.E., J.L. McClelland and the PDP Research Group (1986).
*Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Volume 1: Foundations*, Cambridge, MA: MIT Press - McClelland, J.L., D.E. Rumelhart and the PDP Research Group (1986).
*Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Volume 2: Psychological and Biological Models*, Cambridge, MA: MIT Press - Pinker, Steven and Mehler, Jacques (1988).
*Connections and Symbols*, Cambridge MA: MIT Press. - Jeffrey L. Elman, Elizabeth A. Bates, Mark H. Johnson, Annette Karmiloff-Smith, Domenico Parisi, Kim Plunkett (1996).
*Rethinking Innateness: A connectionist perspective on development*, Cambridge MA: MIT Press.

In this course, we will focus on papers that were central to the Connections vs Symbol debate. The Fodor & Pylyshyn (1988) paper raised a principled objection to Connectionnism in terms of the expressive and computational capacity of these models in order to adequately address language and thought processes. The two other papers: the recurrent networks (Elman, 1990), and the tensor products (Smolensky, 1990) are technical contribution which address some of the criticism of Fodor and Pylyshyn.

In this course, the students will present two of these papers; a small group will present the central argument of the paper, and the rest of the studentw will prepare questions.

__To read and to prepare:__

- Fodor, J.A. & Pylyshyn, Z. (1988). Connectionnism and cognitive architecture: a critical analysis.
*Cognition*,*28*, 3-71. - Elman, J.L. (1990). Finding structure in time.
*Cognitive Science*,*14*, 179-211. - Smolensky, P. (1990). Tensor product variable binding and the representation of symbolic structure in connectionnist systems.
*Artificial Intelligence*,*46*, 159-216.

After the discussion of the papers, we will briefly review some of the more recent theoretical development on the question "what is thought?" as well as the status of the connection/symbol debate today.

__Download PDF of session 2__

__Further readings__

- Smolensky, P. & Legendre, G. (2006).
*The Harmonic Mind: From Neural Computation To Optimality-Theoretic Grammar Vol. 1: Cognitive Architecture; vol. 2: Linguistic and Philosophical Implications*. MIT Press.