Language Evolution and Computation Bibliography

Fluid Construction Grammar (FCG) is an open-source computational grammar formalism that is becoming increasingly popular for studying the history and evolution of language. This demonstration shows how FCG can be used to operationalise the cultural processes and cognitive mechanisms that underly language evolution and change.

The question how a shared vocabulary can arise in a multi-agent population despite the fact that each agent autonomously invents and acquires words has been solved. The solution is based on alignment: Agents score all associations between words and meanings in their lexicons and update these preference scores based on communicative success. A positive feedback loop between success and use thus arises which causes the spontaneous self-organization of a shared lexicon. The same approach has been proposed for explaining how a population can arrive at a shared grammar, in which we get the same problem of variation because each agent invents and acquires their own grammatical constructions. However, a problem arises if constructions reuse parts that can also exist on their own. This happens particularly when frequent usage patterns, which are based on compositional rules, are stored as such. The problem is how to maintain systematicity. This paper identifies this problem and proposes a solution in the form of multilevel alignment. Multilevel alignment means that the updating of preference scores is not restricted to the constructions that were used in the utterance but also downward and upward in the subsumption hierarchy.

This paper compares two prominent approaches in artificial language evolution: Iterated Learning and Social Coordination. More specifically, the paper contrasts experiments in both approaches on how populations of artificial agents can autonomously develop a grammatical case marking system for indicating event structure (i.e. `who does what to whom'). The comparison demonstrates that only the Social Coordination approach leads to a shared communication system in a multi-agent population. The paper concludes with an analysis and discussion of the results, and argues that Iterated Learning in its current form cannot explain the emergence of more complex natural language-like phenomena.

Semantic maps have offered linguists an appealing and empirically rooted methodology for describing recurrent structural patterns in language development and the multifunctionality of grammatical categories. Although some researchers argue that semantic maps are universal and given, others provide evidence that there are no fixed or universal maps. This paper takes the position that semantic maps are a useful way to visualize the grammatical evolution of a language (particularly the evolution of semantic structuring) but that this grammatical evolution is a consequence of distributed processes whereby language users shape and reshape their language. So it is a challenge to find out what these processes are and whether they indeed generate the kind of semantic maps observed for human languages. This work takes a design stance towards the question of the emergence of linguistic structure and investigates how grammar can be formed in populations of autonomous artificial agents that play language games with each other about situations they perceive through a sensori-motor embodiment. The experiments reported here investigate whether semantic maps for case markers could emerge through grammaticalization processes without the need for a universal conceptual space.

Pronouns form a particularly interesting part-of-speech for evolutionary linguistics because their development is often lagging behind with respect to other changes in their language. Many hypotheses on pronoun evolution exist -- both for explaining their initial resilience to change as well as for why they eventually cave in to evolutionary pressures -- but so far, no one has proposed a formal model yet that operationalizes these explanations in a unified theory. This paper therefore presents a computational model of pronoun evolution in a multi-agent population; and argues that pronoun evolution can best be understood as an interplay between the level of language strategies, which are the procedures for learning, expanding and aligning particular features of language, and the level of the specific language systems that instantiate these strategies in terms of concrete words, morphemes and grammatical structures. This claim is supported by a case study on Spanish pronouns, which are currently undergoing an evolution from a case- to a referential-based system, the latter of which there exist multiple variations (which are called leismo, laismo and loismo depending on the type of change).

This paper is part of an ongoing research program to understand the cognitive and functional bases for the origins and evolution of spatial language. Following a cognitive-functional approach, we first investigate the cross-linguistic variety in spatial language, with special attention for spatial perspective. Based on this language-typological data, we hypothesize which cognitive mechanisms are needed to explain this variety and argue for an interdisciplinary approach to test these hypotheses. We then explain how experiments in artificial language evolution can contribute to that and give a concrete example.

Construction grammar theories argue that the selection and realization of a verb's arguments is largely taken care of by constructions, as opposed to lexicalist theories which constrain the argument structure of a verb in the lexicon. So far, however, no operational definition has been given which shows how this 'fusion' of a verb's arguments with the roles of a construction can be achieved. This paper reports a fully implemented solution in Fluid Construction Grammar in which the lexical entry of the verb lists its 'potential valences' from which constructions can select.

This paper shows how experiments on artificial language evolution can provide highly relevant results for important debates in linguistic theories. It reports on a series of experiments that in- vestigate how semantic roles can emerge in a population of artificial embodied agents and how these agents can build a network of constructions. The experiment also includes a fully oper- ational implementation of how event-specific participant-roles can be fused with the semantic roles of argument-structure constructions and thus contributes to the linguistic debate on how the syntax-semantics interface is organized.

Case languages use an inflectional category system for marking event structure. The research in this thesis investigates how such a grammatical system can be developed as the consequence of distributed processes whereby language users continuously shape and reshape their language in locally situated communicative interactions. Since these processes are notoriously difficult to grasp in natural languages, this thesis offers additional evidence from computational simulations in which autonomous artificial agents self-organise a case-like grammar with similar properties as found in case languages such as German, Latin and Turkish.

This thesis hypothesises that language users gradually build their grammar in order to optimise their communicative success and expressiveness while at the same time reducing the cognitive effort needed for semantic interpretation. In the experiments, artificial agents engage in a series of `language games' in which the speaker has to describe a dynamic event to the hearer. The agents are equipped with diagnostics for autonomously detecting communicative problems, repair strategies for solving these problems, and alignment strategies for coordinating their linguistic inventories with each other. Through comparative simulations, this thesis aims at demonstrating which communicative and external pressures and which cognitive mechanisms are minimally required for the formation of a case grammar.

Two innovating experiments are reported. The first experiment offers the first multi-agent simulations ever that involve polysemous categories. The agents are capable of inventing grammatical markers for indicating event structure and of generalising these markers to semantic roles by performing analogical reasoning over events. Extension by analogy occurs as a side-effect of the need to optimise communicative success and is accompanied by careful abstraction, which yields an increased productivity of the categories. In the second experiment, the agents are capable of combining markers into larger argument structure constructions through pattern formation. The results show that languages become unsystematic if the linguistic inventory is unstructured and contains multiple levels of organisation. This thesis demonstrates that this problem of systematicity can be solved using multi-level selection.

All the experiments are implemented in Fluid Construction Grammar. This thesis presents the first computational formalisation of argument structure in a construction-based approach that works for both production and parsing. It implements the `fusion' of the participant roles of events with the semantic roles of argument structure constructions. This representation aims at maximal fluidity and introduces some novel concepts in linguistics. Instead of containing a fixed predicate frame, verbs list their `potential valents' from which the `actual valency' is selected by argument structure constructions.

Even though the experiments involve the formation of artificial languages, the results are highly relevant for natural language research as well. This thesis therefore engages in an interdisciplinary dialogue with linguistics and contributes to some currently ongoing debates such as the formalisation of argument structure in construction grammar, the organisation of the linguistic inventory, the status of semantic maps and thematic hierarchies and the mechanisms for explaining grammaticalization.

Language can be viewed as a complex adaptive system which is continuously shaped and reshaped by the actions of its users as they try to solve communicative problems. To maintain coherence in the overall system, different language elements (sounds, words, grammatical constructions) compete with each other for global acceptance. This paper examines what happens when a language system uses systematic structure, in the sense that certain meaning-form conventions are themselves parts of larger units. We argue that in this case multi-level selection occurs: at the level of elements (e.g. tense affixes) and at the level of larger units in which these elements are used (e.g. phrases). Achieving and maintaining linguistic coherence in the population under these conditions is non-trivial. This paper shows that it is nevertheless possible when agents take multiple levels into account both for processing meaning-form associations and for consolidating the language inventory after each interaction.