Case has fascinated linguists for centuries without however revealing its most important secrets. This paper offers operational explanations for case through language game experiments in which autonomous agents describe real-world events to each other. The experiments demonstrate (a) why a language may develop a case system, (b) how a population can self-organize a case system, and (c) why and how an existing case system may take on new functions in a language.

Abstract. 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.

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Natural languages are fluid. New conventions may arise and there is never absolute consensus in a population. How can human language users nevertheless have such a high rate of communicative success? And how do they deal with the incomplete sentences, false starts, errors and noise that is common in normal discourse? Fluidity, ungrammaticality and error are key problems for formal descriptions of language and for computational implementations of language processing because these seem to be necessarily rigid and mechanical. This chapter discusses how these issues are approached within the framework of Fluid Construction Grammar. Fluidity is not achieved by a single mechanism but through a combination of intelligent grammar design and flexible processing principles.

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