Robert M. French

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The role that consciousness plays in cognition is one of the most central and long-standing issues in experimental psychology. Differences between conscious and unconscious processing have indeed been explored in many different fields, such as memory (e.g., Jacoby, 1991; see also Kinoshita, 2001), perception (Reingold & Merikle, 1988), conditioning (Clark &(More)
connectionist networks, such as their difficulties with sequence-learning and the profoundly stimulus–response nature of supervised learning algorithms such as error backpropagation had been largely solved. However, as these problems were being solved, another was discovered by McCloskey and Cohen1 and Ratcliff 2. They suggested that there might be a(More)
High-level perception—the process of making sense of complex data at an abstract, conceptual level—is fundamental to human cognition. Through high-level perception, chaotic environmental stimuli are organized into the mental representations that are used throughout cognitive processing. Much work in traditional artificial intelligence has ignored the(More)
Our ability to see a particular object or situation in one context as being “the same as” another object or situation in another context is the essence of analogy-making. It encompasses our ability to explain new concepts in terms of already-familiar ones, to emphasize particular aspects of situations, to generalize, to characterize situations, to explain(More)
In order to solve the “sensitivity-stability” problem — and its immediate correlate, the problem of sequential learning — it is crucial to develop connectionist architectures that are simultaneously sensitive to, but not excessively disrupted by, new input. French (1992) suggested that to alleviate a particularly severe form of this disruption, catastrophic(More)
This paper draws on previous research that strongly suggests that bilingual memory is organized as a single distributed lexicon rather than as two separately accessible lexicons corresponding to each language. Interactive-activation models provide an effective means of modeling many of the cross-language priming and interference effects that have been(More)
In connectionist networks, newly-learned information destroys previously-learned information unless the network is continually retrained on the old information. This behavior, known as catastrophic forgetting, is unacceptable both for practical purposes and as a model of mind. This paper advances the claim that catastrophic forgetting is a direct(More)
All natural cognitive systems, and, in particular, our own, gradually forget previously learned information. Consequently, plausible models of human cognition should exhibit similar patterns of gradual forgetting old information as new information is acquired. Only rarely (see Box 3) does new learning in natural cognitive systems completely disrupt or erase(More)
Individuals of all ages extract structure from the sequences of patterns they encounter in their environment, an ability that is at the very heart of cognition. Exactly what underlies this ability has been the subject of much debate over the years. A novel mechanism, implicit chunk recognition (ICR), is proposed for sequence segmentation and chunk(More)