28.2019, Review: Cog Sci; Comp Ling: van Trijp (2016)

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LINGUIST List: Vol-28-2019. Mon May 01 2017. ISSN: 1069 - 4875.

Subject: 28.2019, Review: Cog Sci; Comp Ling: van Trijp (2016)

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Date: Mon, 01 May 2017 12:29:11
From: Daniel Walter [dwalter at andrew.cmu.edu]
Subject: The evolution of case grammar

 
Discuss this message:
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Book announced at http://linguistlist.org/issues/27/27-2838.html

AUTHOR: Remi  van Trijp
TITLE: The evolution of case grammar
SERIES TITLE: Computational Models of Language Evolution
PUBLISHER: Language Science Press
YEAR: 2016

REVIEWER: Daniel Walter, Emory University

Reviews Editor: Helen Aristar-Dry

SUMMARY

In The Evolution of Case Grammar, Remi van Trijp puts forth a computationally
plausible program that outlines the evolution of case grammar in a
communicative network of artificial agents. The book is organized into five
chapters. The first two, “Case and artificial language evolution” and
“Processing case and argument structure” provide necessary background
information for the experiments outlined in the following two chapters,
“Baseline experiments” and “Multi-level selection and language systematicity”.
The final chapter, “Impact on artificial language evolution and linguistic
theory” explains the relevance of the experimental findings to other
computational models of language evolution, as well as linguistics more
generally.

In the first chapter, “Case and artificial language evolution”, van Trijp
poses two important questions regarding case and language evolution:

1. Why do some languages evolve a case system?
2. How can a population self-organize a case system?

According to the author, neither of these questions has been answered by
traditional linguistics, and the lack of raw historical data makes it unlikely
that an answer can be found by exploring natural languages. Along this line of
reasoning, the author argues for agent-based modeling, or the creation of a
virtual environment with artificial agents that can operate at a pace which
dramatically shrinks the timeline needed to observe evolutionary change. The
author then switches topics to an overview of case. The author indicates that
there are two primary functions of case within a language; to indicate event
structure and package information structure. He also argues that there are
four stages of case marking: no marking, specific marking, semantic roles, and
syntactic roles. In the third section of the first chapter, the author changes
topics from case to modeling language evolution. He presents three possible
models. The first model is a model of genetic evolution, which focuses mainly
on selective pressures and fitness. In this model, parent-agents pass on
language genomes to their offspring-agents. It is at the stage of transmission
that variation takes place in the form of mutations. The second type of model
presented is an Iterated Learning Model (ILM) where language is transmitted
from one generation to the next culturally, rather than genetically endowed.
Unlike the previous model, there is no reliance on functional pressures. This
model is highly representative of a generative approach to language
acquisition. The third model “views the task of building and negotiating a
communication system as a kind of problem-solving process” (pg. 12) and
reflects cognitive-functional and usage-based theories of language learning.
The author emphasizes that these models are not necessarily mutually exclusive
but submits that his research agenda most closely follows the third model.
After describing the models, the author describes the do’s and don’ts of this
type of work. In the final section, van Trijp provides an overview of previous
work, including the emergence of adaptive lexicons and the basis of “Fluid
Construction Grammar” (FCG). The author prescribes FCG as the primary language
learning theory for this book, which he defines as common construction grammar
(Croft, 2005) but with an added emphasis on the fluidity of language emergence
across linguistic units. The author expands upon FCG further in the second
chapter.

In the second chapter, “Processing case and argument structure”, van Trijp
begins with an appeal to processing models that incorporate both parsing and
production, specifically FCG. FCG is designed to be bidirectional. That is to
say, and FCG-system is built to be capable of both processing an utterance it
receives as well as producing a meaningful utterance it is asked to convey.
The underlying representational system is similar to connectionist models,
where the connections between nodes representing different features of the
language are updated based on probabilities built from input and experience.
One of the primary issues to understand is the coupled feature structure. In
FCG, all linguistic knowledge is represented in a coupled feature structure
with a semantic pole and a syntactic pole. Within this system, the primary
function of the program is to ‘unify’ and ‘merge’. These two operations are
meant to satisfy the conditions for parsing and production, in which syntactic
and semantic features unify and merge to produce new coupled feature
structures. In addition to ‘unify’ and ‘merge’, FCG also requires a special
operator, called the ‘J-operator’. This operator allows for the specification
of hierarchical relations between units. In the final section of the chapter,
the author provides an example of how the FCG system would parse the phrase
‘jack sweep dust off-floor’, and produce the phrase ‘jack sweep floor’. In
this section, it is necessary to understand how the different nodes are being
bound together. To put it simply, the system already has access to a list of
vocabulary and a list of possible semantic constructions. It is the job of the
system to merge the vocabulary items with the semantic constructions and check
that the meanings and forms stored and those produced match before a new node
is created. Each construction is endowed with valences for the possible number
of lexical items with which it can merge. The major hurdle that this type of
system faces, which will be the motivation for case marking, is that there is
no syntax inherent in the constructions. The order of the lexical items is not
relevant for the system to comprehend an utterance, since lexical items match
with the construction roles. Therefore ‘jack sweep floor’ and ‘jack floor
sweep’ and ‘floor jack sweep’ are all perfectly intelligible to the system. It
is simply a reliance on the order in the input that makes one more
conventionalized. Finally, as lexical entries are used within certain
constructions, they gain a specific confidence score which helps
conventionalize the links between a particular lexical entry and a semantic
construction.

In the third chapter, “Baseline experiments”, van Trijp begins to describe the
experiments he conducted using an FCG-based system which describes how a
population of agents can evolve grammar over time. The input to the system is
based on input from a real-world puppet theater in which physical agents
(puppets) interact with objects and other puppets which provide the set of
constructions which the computer agents need to communicate and comprehend. In
addition to the physical environment, the agents themselves are endowed with
particular abilities, such as social and cooperative behavior and a predefined
lexicon, but no grammar. In the first baseline experiment, the agents have
only a diagnostic feature which allows them to link lexical items to
constructions, but not to mark the relationships between words. This
experiment was run twice. First with only two agents, and second with a
population of 10 agents. Results are discussed in terms of communicative
success, i.e. whether the ‘hearer’ agent signals agreement or disagreement
with the scenario to which both gave attention, and cognitive effort, i.e. the
number of inferences the ‘hearer’ needs to make in order to successfully
understand the ‘speaker’. The results of the first experiment show that after
10 series of 500 language games, the average communicative success reached
approximately 70% and the maximum cognitive effort (on a scale from 0 to 1)
was a 0.6. This indicates that while the communicators were successful more
often than not, a large amount of cognitive effort was needed and much room
for improvement exists. In the second baseline experiment, agents are endowed
with a repair strategy that allows them to create role-specific marking in
order to optimize communication. This innovation and expansion is
proceduralized through a re-entrance process. The experiment is run with 2, 5,
and 10 agent populations. Unlike the results from baseline-experiment 1, in
which communicative success and cognitive effort remained steady throughout
the 500 language games, the results of this experiment show change over time
in a pattern closely related to a power function. In all three population
scenarios, communicative success reaches 100%, and cognitive effort drops to
0.0. The time required for this to occur is longer the more agents are
involved. In this experiment, the author also tracks the number of unique
markers needed to achieve this success. Competition between forms for marking
roles in particular contexts is also occurring, but since these markers are
created and developed in a local context with a particular context and lexical
item, the total number of role markers needed is relatively high compared to
the number of generalizable contexts. In the final baseline experiment, the
author notes that if the agents were to continue on with larger populations
and more contexts, the inventory size needed would explode. To solve this
problem, the agents are given the ability of analogical reasoning, for which
the author provides the following algorithm: 1. Given a target participant
role-sub-i, find a source role-sub-j for which a case marker already exists;
2. Elaborate the mapping between the two; 3. Keep the mapping if it is good;
4. If there are multiple analogies possible, choose the best one (based on
entrenchment and category size); and 5. Build the necessary constructions and
make the necessary changes to existing items. In the final experiment, there
are four different trials. In trials 4a and 4b, the only difference is the
size of the population, 2 and 10 respectively. In both of these experiments,
the populations succeed in achieving 100% communicative success and 0.0
cognitive effort, but the number of markers during the innovation and learning
stage fails to align within the population and decrease over time. In set-up
3c, the agents are also given the ability to track co-occurrences. This time
agents begin to align after the innovation and learning phase and the total
number of markers needed for comprehension decreases over the number of
language games. The author notes, however, that the gain in inventory
optimization is minimal, since the agents end up with an average of 25 markers
for 30 total participant roles. In set-up 3d, the agents rely solely on token
frequency of successful interactions instead of the co-occurrence links and
confidence scores. The results indicate persistent variation during the phase
in which the agents should be aligning to a common set of markers. The results
indicate that while communicative success and cognitive effort can be
optimized, the resulting system does not mirror that of natural languages.
Namely, there is no optimization of the total number of markers needed and no
generalization of markers across constructions. The author argues for a
dynamic representation of categories and word meanings and the ability of
agents to do one-to-many or even many-to-many mappings of markers to roles,
which he believes can be achieved through coordination and pattern formation.

In Chapter Four, ‘Multi-level selection and language systematicity’, van Trijp
presents an argument for the need for a dynamic, multi-level selection process
to overcome the issue of systematicity that many artificial languages lose
once smaller patterns begin to combine with larger ones. The chapter begins
with an overview of pattern formation in natural languages, which includes an
in depth look at negation in French. The material here dives into whether this
evolution in French is the result of reanalysis or pattern formation. The
author falls on the side of pattern formation as the more likely culprit for
this language change and argues that computational models can show their 
merit in this arena by demonstrating the consequences of each hypothesis. The
author then moves to a description of what pattern formation would look like
computationally, which is then employed in the following experiments. In
experiment 1, the setup is the same as in experiment 2c, in that there is
individual selection without analogy, but the agents are endowed with a new
diagnostic and repair strategy for pattern formation. With this new strategy,
agents create and converge on one construction for each possible meaning, not
one marker. The results show that the acquisition of constructions happens
quickly, but alignment of constructions lasts a relatively long time. This is
calculated as a meaning-form coherence score. In this experiment, the
population almost reaches 100% for this score, but one or two forms are still
undecided, even after 16,000 language games. The author argues that the agents
are incapable of constructing a systematic language because the agents treat
constructions as independent linguistic items. The importance for case
markers, as indicated by the author, is that “this results in some case
markers losing the competition for marking a certain participant role on the
level of a single-argument constructions but still becoming the most
successful one as part of a larger pattern” (pg. 125). The author then
continues this discussion with the lack of systematicity in other work, such
as exemplar-based simulations, probabilistic grammars, and Iterated Learning
Models (ILMs). In experiment 2, the author tries to overcome the systematicity
problem by providing the agents with a multi-level alignment strategy, but
still without analogy. In this multi-level strategy, when a game is
successful, the hearer not only increases the score of the applied
constructions, but also those of the related constructions, while punishing
competing constructions through lateral inhibition. The results of three
different strategies (top-down, bottom-up, and multi-level) show that with the
multi-level selection strategy, all ten agents share the same form-meaning
mapping preferences after only 7,000 language games. In addition, the agents
agree upon 30 case markers for the 51 possible constructions. The final
experiment builds on the previous one by adding the ability for analogy to the
multi-level selection strategy. The results are a comparison of five set-ups:
individual, top-down, and bottom-up selection, multi-level selection with the
previous lateral inhibition mechanism, and finally multi-level selection
without lateral inhibition, but rather an algorithm for memory decay. To
begin, the author compares the first four. The results indicate that the
multi-level selection is the fastest to achieve 100% communicative success and
0.0 cognitive effort, as well as the only one to achieve a fully systematic
language. However, the number of specific case markers is still over 20 and
only five were generalized to multiple roles. The author then sums up the
results of the final experimental setup, which shows that the new memory decay
strategy which employs a new alignment strategy focused on re-using existing
markers, as long as there is no conflicting participant role already created.
The results show that this methods ends up with a final count of three
participant roles generalized across constructs, which is a successful
optimization of the meaning space and total participants that the system needs
to address. 

The final chapter, “Impact on artificial evolution and linguistic theory”,
includes a comparison of this approach to others, with a particular focus on
the Iterated Learning Model. The author focuses primarily on issues of
systematicity, and the need of ILM to incorporate innate language skills in
order to succeed. In contrast, van Trijp’s model reduces the need for an
innate language acquisition device. He also makes distinct comparisons between
this model and other argument and construction grammar models, such as the
Berkeley Construction Grammar (Kay & Fillmore, 199) and Sign-Based
Construction Grammar (Fillmore et al., unpublished). The author compares his
model’s ability to explain ditransitive in English constructions as compared
to these other construction grammar theories. The author concludes with a
summary of this research agenda’s contributions to linguistics and further
directions of study, and an emphasis on continuing to look at both frequency
and function in linguistic evolution.

EVALUATION

Van Trijp provides an in depth perspective on language evolution, which
Christiansen and Kirby (2003) dubbed one of the hardest problems in science,
and the ways in which computational linguistics can contribute to our
knowledge. Most importantly, his focus is on testing the mechanisms which make
language evolution possible, in contrast to other fields of study that assume
some type of language acquisition device or black box, in which the operations
and actual processes which transform language over time are not within the
scope of study. Understanding language mechanisms and how they operate over
time, across cognitive space, and with one another is crucial to creating a
model of language that can account for processing and production. 

Van Trijp’s clear discussion of previous work, and the detailed account of his
methods is essential to is accessibility to those who are not working directly
in computational models of language. While some basic knowledge of coding
would be beneficial for someone interested in this work, especially when
looking at the proceduralization of particular algorithms into code, it is not
absolutely necessary. Also, for those who are interested in computational
work, van Trijp’s description of case and its function within natural
languages allows for an easy understanding of the relevance of this work to
all of linguistics. 

Another important insight into his work is its ability to account for the
development in case over time while still achieving comprehension accuracy and
decreasing the cognitive load on the individual. Some may argue that the
scoring system for cognitive load might need a more fine-grained approach to
be more life-like, but for this work, it is successful in at least capturing
the phenomenon in a computationally significant way. The later experiments in
this book build off of the previous work, which took into account neither
systematicity nor lexicon size optimization. In these later experiments, the
author shows how a more detailed, multi-level alignment strategy, along with
analogical reasoning, were able to take on both systematicity and lexicon
optimization. The results provide a clear understanding of the types of
cognitive mechanisms necessary to achieve case systems akin to those of
natural languages in a very convincing manner.

As for audience, this book is intended for researchers and scholars in
computational linguistics, but a more general audience of scholars in
linguistics more broadly would also benefit from the insights resulting from
this type of experimental approach to language evolution. Any researcher in
linguistics would benefit from learning more about how computational methods
can be used to prove theories about underlying and invisible mechanisms of
language learning, processing, production, and evolution. In addition, the
detailed manner in which coding is described and laid out provides something
of a roadmap for those who are looking to conduct similar experiments.

In sum, van Trijp’s book does an excellent job of providing access to a
complex research area. His efforts in describing not only what he did, but
also his justifications allow readers a deeper understanding of the
assumptions researchers in computational linguistics need to make. Van Trijp
weaves together a long studied area of linguistics with a novel approach using
computational models and discusses the relevance of his results not only for
computational linguistics, but to linguistics more generally.

REFERENCES

Christiansen, M. & Kirby, S. (2003). Language evolution: The hardest problem
in science? In Morten Christiansen & Simon Kirby (eds.), Language evolution,
1-15. Oxford: Oxford University Press. 

Croft, W. (2005). Logical and typological arguments for radical construction
grammar. In Jan-Ola Östman & Mirjam Fried (eds.), Construction grammars:
Cognitive grounding and theoretical extensions, 273-314. Amsterdam: John
Benjamins.

Fillmore, C., Kay, P., Michaelis, L., & Sag, I. unpubl. Construction grammar.
Unpublished manuscript. Chapter 7 available online at
http://lingo.stanford.edu/sag/SBCG/7.pdf. Chicago: Chigaco University Press.

Kay, P. & Fillmore, C. (1999). Grammatical constructions and linguistic
generalizations: The what’s X doing Y? Construction. Language 75, 1-33.


ABOUT THE REVIEWER

Dr. Walter is a Visiting Assistant Professor of German and English at Emory
University's Oxford Campus, where he teaches German, English composition, and
linguistics. His research interests include the acquisition of second language
case marking, German as a foreign language, and the interplay between language
learning mechanisms in foreign language acquisition. His publications focus
primarily on case marking in German by adult foreign language learners, but he
is also interested in understanding the role of entrenchment in the
acquisition of case markers and the effect of developing concepts to overcome
challenges to case acquisition in various languages. He is especially
interested in understand the relationship between case forms and their
acquisition in cross-linguistic comparisons.





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