Connectionist Modeling of Experience-based Effects in Sentence ...

Chapter 1 Preliminaries
empirically consistent, as comparisons with studies like King and Just (1991) show. All
predicted processing difficulties are explained by demand of activation. This also covers
individual differences by ascribing them to different limits of the total activation amount.
The effect of decay is only indirectly accounted for, depending on the number of newly
activated elements, which is very similar to the DLT Integration Cost. The capacity
limit causes newly needed activation to be preferably drawn from older elements. This
results in a continuously graded decay, which, however, is not temporally dependent but
rather depends on storage/processing demands just like in the DLT.
ACT-R Sentence Processing Model
Another computationally implemented sentence processing model (Lewis and Vasishth,
2005; Lewis et al., 2006; Vasishth and Lewis, 2006b) is built on the cognitive architecture
ACT-R (Anderson and Lebiere, 1998; Anderson et al., 2004). Similar to the CAPS
model ACT-R works on a sub-symbolic activation propagation basis. Rule application,
however, happens on a more symbolic-fashioned condition-action relation. Processing
difficulties are predominantly retrieval-based. Elements (memory chunks) like lexical
entries involved in a production need to be retrieved from declarative memory. The
success of the retrieval process depends on the chunk’s current activation level and its
matching of the retrieval cues specified in the production condition. Retrieval cues
are feature value pairs that increase the activation of chunks depending on the number of
matched features (associative activation). The total activation of a memory chunk
calculated from the activation level and cue-based activation determines the probability
of being retrieved and its retrieval latency. The possibility of several chunks matching
the retrieval cues partially enables the model to simulate associative retrieval
interference. Retrieval interference causes distribution of associative activation onto
several lexical entries, causing latencies and potentially the retrieval of the wrong chunk.
How severely interference affects retrieval depends on the beforementioned activation
level. Activation is a fluctuating value which is a function of usage and decay over time.
Cue-based activation and retrieval of a particular element cause its reactivation that
slows down the decay process. The parsing process of the ACT-R sentence processing
model (Lewis and Vasishth, 2005) is a combination of a left corner incremental structure
building mechanism and a top-down goal-guided syntactic expectation that specifies the
phrasal category of the structure to be constructed. A very unconventional assumption
of the model regarding the parsing process is that, in spite of an incremental parsing
process, the memory representation does not contain serial order information that could
guide retrieval and attachment preferences. Recency is only implicitly accounted for
by the decay function that affects parsing decisions in addition to cue-matching. What
differentiates this model from CC-READER and DLT is the account for interference
effects and a temporal decay function. Furthermore, processing difficulty is not represented
by processing cycles but directly by estimated processing time. Setting retrieval
cues, structural attachment, and shifting attention to the next word have fixed time
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