After several decades in scientific purgatory, language evolution has reclaimed its place as one of the most important branches in linguistics. This renewed interest is accompanied by powerful new methods for making empirical observations. At the same time, construction grammar is increasingly embraced in all areas of linguistics as a fruitful way of making sense of all these new data, and it has enthused formal and computational linguists, who have developed sophisticated tools for exploring issues in language processing and learning. Separately, linguists and computational linguists are able to explain which changes take place in language and how these changes are possible. When working together, however, they can also address the question of why language evolves over time and how it emerged in the first place. This special issue therefore brings together key contributions from both fields to put evidence and methods from both perspectives on the table.
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.
Linguistic utterances are full of errors and novel expressions, yet linguistic communication is remarkably robust. This paper presents a double-layered architecture for open-ended language processing, in which ?diagnostics? and ?repairs? operate on a meta-level for detecting and solving problems that may occur during habitual processing on a routine layer. Through concrete operational examples, this paper demonstrates how such an architecture can directly monitor and steer linguistic processing, and how language can be embedded in a larger cognitive system.
Cognitive linguistics has reached a stage of maturity where many researchers are looking for an explicit formal grounding of their work. Unfortunately, most current models of deep language processing incorporate assumptions from generative grammar that are at odds with the cognitive movement in linguistics. This demonstration shows how Fluid Construction Grammar (FCG), a fully operational and bidirectional unification-based grammar formalism, caters for this increasing demand. FCG features many of the tools that were pioneered in computational linguistics in the 70s-90s, but combines them in an innovative way. This demonstration highlights the main differences between FCG and related formalisms.
This chapter explores a possible language strategy for verbalizing aspect: the encoding of Aktionsarten by means of morphological markers. Russian tense-aspect system is used as a model. We first operationalize this system and reconstruct the learning operators needed for acquiring it. Then we perform a first language formation experiment in which a novel system of Aktionsarten emerges and gets coordinated between the agents, driven by a need for higher expressivity.
Grammatical agreement is one of the most puzzling aspects found in natural language. Its acquisition requires intensive linguistic exposure and capacities to deal with outliers that break regular patterns. Other than relying on statistical methods to deal with agreement in a computational application, this paper demonstrates how agreement can be learned by artificial agents in a simulated environment in such a way that the openendedness of natural language can be captured by their language processing mechanisms.