Elman, J.L. (1995) Language as a dynamical system. In Mind as Motion (Port, R.F. and van Gelder, T., eds), pp. 195--225, MIT Press  Home/Search   Document Details and Download   Summary   Related Articles   Check

....sequence is input to the network, one word at a time. The network is trained to predict the next word from the current stream of input words. He claims that this network can discover word segmentation and lexical classes [8] word clustering [9] and 22 grammar with sentence embedding sentence [10]. This configuration (we call temporal configuration) has an advantage over spatial configuration in the following points. First, the context layer works as a memory of the past inputs. Although the context layer seems to keep only the previous state of the network, it is calculated using one ....

....by shift operators. Dividing x by 2 is equivalent to right shift operation, that is, x i 1 x i ; Multiplication of x by 2 is the reversal operation. Combination of these operators can form a push down stack, which is suitable for handling nested information. It is notable that Elman [10] is standing on this point of view. He claims that a simple recurrent network trained with center embedding sentences can generalize the rule to more deeper nestings of center embeddings, because such a network learns to store information of the embedding (outer) sentence into smaller portion of ....

Je#rey L. Elman. Language as a dynamical system. In R. F. Port and T. van Gelder, editors, Mind as Motion: Explorations in the Dynamics of Cognition, pages 195--225. MIT Press, Cambridge, MA, 1995. (cited in pages 23, 44)

....non recurrent feedforward networks, since the previous context in recurrent networks has an important dynamic influence within these networks. The internal states in re current networks do not only depend on the input but also on the internal state of the local mem ory based on previous inputs [Elman, 1995, Giles and Omlin, 1993, Omlin and Giles, 1996] For this reason, to date the focus has been primarily on smaller recurrent networks and artificially generated data. For instance, an interesting current approach interprets the training of a SRN network that has two input, two output and two ....

Elman, J. L. (1995). Language as a dynam- ical system. In Port, P. F. and van Gelder, T., editors, Mind as motion: explorations in the dynamics of cognition, pages 195-225. JIT, Cambridge, JA.

....form a hierarchy of analog computers with varying sets of elementary operations. We show below that dynamical recognizers can be thought of as off line BSS machines with constant space. Finally, recurrent neural networks are being studied as models of language recognition [31] for regular [12], context free [10, 12] and context sensitive [34] languages, as well as fragments of natural language [ where grammars are represented dynamically rather than symbolically. The results herein then represent upper and lower limits on the grammatical capabilities of such networks in real time, ....

....of analog computers with varying sets of elementary operations. We show below that dynamical recognizers can be thought of as off line BSS machines with constant space. Finally, recurrent neural networks are being studied as models of language recognition [31] for regular [12] context free [10, 12], and context sensitive [34] languages, as well as fragments of natural language [ where grammars are represented dynamically rather than symbolically. The results herein then represent upper and lower limits on the grammatical capabilities of such networks in real time, with varying sorts of ....

J. Elman, "Language as a dynamical system." In R.F. Port and T. van Gelder (Eds.), Mind as Motion: Explorations in the Dynamics of Cognition. MIT Press, 1995.

....a good object for hired rather than a binary contrast between two biases (Good Agent vs. Good Patient) To this end, it is also important to address the question of how to represent phrase structural relationships as well as simple contrasts between states in a finite state language. Wiles and Elman, 1995), Rodriguez et al. to appear) and Tabor (1998) provide some insight into this problem by looking at how SRNs and related devices can represent context free grammars. Here, a central question is, How should the learning mechanism generalize from its finite training experience to an infinite state ....

Elman, J. (1995). Language as a dynamical system. In Port, R. and van Gelder, T., (Eds.) Mind as Motion: Explorations in the Dynamics of Cognition. Cambridge, MA.: MIT Press.

....several examples of dynamic systems approaches to language exist. A number of researchers have investigated motor behavior during speech, An extended version is available as AI MEMO from the VUB AI Lab e.g. Saltzman, 1995] Browman and Goldstein, 1995] Tuller and Kelso, 1990] In [Elman, 1995], an analysis of the activation space of recurrent neural networks is presented as a dynamical view on grammar and embedding. A difference between that work and ours, is that grammar does not play a role here. Instead, the focus here is on the use of language, and concepts are grounded by use in ....

Elman, J. L. (1995). Language as a dynamical system. In Port, R. F. and Van Gelder, T., editors, Mind as Motion: Explorations in the Dynamics of Cognition, chapter 8, pages 195--225. MIT Press.

....of the system described above. In the literature, several other examples of dynamic systems approaches to the investigation of language exist. A number of researchers have investigated motor behavior during speech, e.g. Saltzman, 1995] Browman and Goldstein, 1995] Tuller and Kelso, 1990] In [Elman, 1995], an analysis of the activation space of recurrent neural networks is presented as a dynamical view on grammar and embedding. A difference between that work and ours, is that grammar does not play a role here. Instead, the focus here is on the use of language, and concepts are grounded by use in ....

Elman, J. L. (1995). Language as a dynamical system. In Port, R. F. and Van Gelder, T., editors, Mind as Motion: Explorations in the Dynamics of Cognition, chapter 8, pages 195--225. MIT Press.

....dynamical recognizers can be thought of as off line BSS machines with constant space. Finally, recurrent neural networks are being studied as models of language recognition [36] for regular [16] context free [13, 41] and context sensitive [39] languages, as well as fragments of natural language [14], where grammars are represented dynamically rather than symbolically. The results herein then represent upper and lower limits on the grammatical capabilities of such networks in real time, with varying sorts of nonlinearities. Perhaps these are baby steps toward understanding the cognitive ....

J. Elman, "Language as a dynamical system." In R.F. Port and T. van Gelder (Eds.), Mind as Motion: Explorations in the Dynamics of Cognition. MIT Press, 1995.

....are rational. We study real coefficients in [15] As a partial motivation for this work, we note that recurrent neural networks are being studied as models of language recognition [17] for regular [7] context free [5] and context sensitive [20] languages, as well as fragments of natural language [6], where grammars are represented dynamically rather than symbolically. The results herein then represent upper and lower limits on the grammatical capabilities of such networks in real time, with varying sorts of nonlinearities. 3 A language not in Poly or PieceLin, and its consequences We will ....

J. Elman, "Language as a dynamical system." In R.F. Port and T. van Gelder (Eds.), Mind as Motion: Explorations in the Dynamics of Cognition. MIT Press, 1995.

.... cognitive systems at different levels (Port and Van Gelder 1995; Kelso 1995) such as the level of single neurons (Rinzel and Ermentrout 1989; Marder and Abbott 1995; Guckenheimer, Gueron, and Harris Warrick 1993) motor behaviors (Taga 1995; Collins and Stewart 1993; Beer 1995) and language (Elman 1995). Techniques of researches in artificial life such as evolutionary programming are helpful in exploring what cognitive functions are necessary for behaving in various environments (Belew and Mitchell 1996) This paper is an example of fruitful convergence of these two lines of research. ....

Elman, J. L. (1995). Language as a dynamical system. In R. F. Port and T. Van Gelder (Eds.), Mind as Motion, pp. 195--225. Cambridge, Massachusetts: MIT Press.

.... no ontology can currently do (Rosenstein, Cohen, Schmill and Atkin, 1997) Dynamical representations of physical interactions are easily learned from observations of dynamics (Rosenstein et al. 1997) this is true also of dynamical representations of linguistic constructs (e.g. Regier, 1995; Elman, 1995). The strongest reason to consider dynamics as a foundation for ontologies, I think, is that the knowledge of the youngest humans neonates and infants is produced by interacting physically with the world. Neonates are capable of movement, but nobody credits them with conceptual thought. ....

Elman, J. 1995. Language as a dynamical system. In Mind As Motion, R. F. Port and T.

....such as finite automata, Markov chain, and so on. In this study we use dynamical recognizers, simple and powerful tools for studying dynamical behavior from the view points of cognitive studies. Dynamical recognizers were first discussed by Pollack[8, 10] and have been used independently by Elman [9] studying the dynamical aspects of language. The dynamical recognizer is now generally called the recurrent neural network (RNN) In particular it is called cascaded RNN, which consists of a function and a context network[8] It is quite similar to a two layer neural network, though the ....

J. Elman, "Language as a Dynamical System" in Mind as Motion (eds. R.E.Port and T.van Gelder, MITpress 1995), 195--226.

.... and have the corpus recognize concepts from sensed movement (Rosenstein et al. 1997) Dynamical representations of physical interactions are easily learned from observations of dynamics (Rosenstein et al. 1997) this is true also of dynamical representations of linguistic constructs (Regier 1995; Elman 1995). They are compact in the sense that a single representation can describe dozens of related concepts. They make explicit the manner of movement and thus make fine distinctions between word meanings. The strongest reason to consider dynamics as a foundation for semantics, we think, is that the ....

Elman, J. 1995. Language as a dynamical system. In Port, R. F., and van Gelder, T., eds., Mind as Motion.

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Elman, J.L. (1995) Language as a dynamical system. In Mind as Motion: Dynamical Perspectives on Behavior and Cognition (Port, R. and van Gelder, T., eds), pp. 195 -- 225, MIT Press

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Elman, J.L. (1995) Language as a dynamical system. In Mind as Motion (Port, R.F. and van Gelder, T., eds), pp. 195--225, MIT Press

No context found.

Elman, J. L. (1995). Language as a dynamical system. In R. F. Port, & T. van Gelder (Eds.), Mind as motion (pp. 195-- 225). Cambridge, MA: MIT Press.

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Elman, J. L. (1995). Language as a dynamical system. In R. F.

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J. Elman, "Language as a dynamical system," in Mind as Motion: Explorations in the Dynamics of Cognition, pp. 195--223. MIT Press, 1995.

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Elman J.L, Language as a dynamical system, in: R.F. Port, T. van Gelder, Eds, Mind as motion: explorations in the dynamics of cognition (Cambridge, MA, MIT Press 1995), pp. 195-223

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Elman, J. (1995) Language as a dynamical system. In R. Port & T. van Gelder ed., Mind as Motion: Explorations in the Dynamics of Cognition . Cambridge MA: MIT Press; 195-225.

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Elman, J.L. (1995) Language as a dynamical system, in Mind as Motion: Explorations in the Dynamics of Cognition (Port, R.F. and van Gelder, T., eds), pp. 195--223, MIT Press

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