Linguistic Selection of Language Strategies A Case Study for Colour Joris Bleys1 and Luc Steels1,2 1
Artificial Intelligence Laboratory, Vrije Universiteit Brussel, Brussels, Belgium
[email protected] 2 Sony Computer Science Laboratory, Paris, France
[email protected]
Abstract. Language evolution takes place at two levels: the level of language strategies, which are ways in which a particular subarea of meaning and function is structured and expressed, and the level of concrete linguistic choices for the meanings, words, or grammatical constructions that instantiate a particular language strategy. It is now reasonably well understood how a shared language strategy enables a population of agents to self-organise a shared language system. But the origins and evolution of strategies has so far been explored less. This paper proposes that linguistic selection, i.e. selection driven by communicative success and cognitive effort, is relevant and shows a concrete case study for the domain of colour on how different language strategies may cooperate and compete for dominance in a population.
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Language Strategies and Language Systems
Human languages are complex adaptive systems that are shaped and reshaped by their users, even in the course of a single dialogue [1]. They undergo change in order to remain adaptive to the expressive needs of the community, while maximising communicative success and minimising cognitive effort [2]. The past decade, consider- Fig. 1. Robotic experiments with the Colour Namable progress has been made ing Game. The speaker draws attention to a chip to model the architecture by naming its colour and the hearer points to the and behaviour of ‘linguistic’ chip which has been named. Agents give feedback afagents such that symbolic ter this interaction in order to share and align their colour categories and vocabularies. communication systems with properties similar to human languages may arise through language games [3]. In this paper we will use the Colour Naming Game, where the speaker uses a colour
to draw the attention of the hearer to an object in the world [4]. Two agents drawn randomly from a population are shown a set of Munsell colour chips. The speaker chooses one chip as the topic, categorises the colour of this topic, and then searches in his own private lexicon how this category is named. The hearer gets the name, looks it up in his own lexicon, and then identifies and points to the chip in the context which fits best with the category named. If this is the chip that the speaker had in mind, the game is a success. Otherwise the speaker points to his original choice and the hearer can learn the name and the category expressed by it. Colour Naming is an interesting domain because it has been studied intensely by anthropologists, neuroscientists, and psychologists, and so there is a significant body of empirical data available, including data about the evolution of colour terms and colour categories [5]. These empirical studies of colour naming in humans have shown three facts: (1) There are different strategies by which speakers use colour to draw attention to objects in the world. One common strategy, which has been studied the most, is to use a limited set of basic colour prototypes utilising the full colour space, meaning the two hue opponent channels and brightness (for example: black, white, red, green, blue, yellow, pink, purple, brown, orange) [6]. We further call this the Basic Colour Strategy. Another strategy is to use only brightness, with words like “dark”, “shiny”, or “light”. We will call this the Brightness Colour Strategy. There are still other possibilities: to combine two basic colour prototypes (as in “bluish green” or “reddish orange”), to suggest colours by naming an object that typically has the colour (as in “lila” or “almond”), to combine the latter with basic colours as in “grass green”, “milk white” or “sky blue”, etc. (2) There is considerable variation in the way in which a particular strategy is instantiated in a language and how it determines how languages change over time. For example, “red” is the name of a prototypical colour in English, roughly in the 625-740 nanometer range of the colour spectrum, but it used to be called “read” in Old English. The same colour prototype is called “rojo” in Spanish, “aka” in Japanese, “ˇcerven´ y” in Czech, or “merah” in Indonesian. The basic colour prototypes used in different languages vary as well and there is also evolution, usually towards more and more refined colour prototypes [6]. For example, English speakers make a rather clear distinction between green and blue, but in Chinese and Japanese there is a single colour category which covers both areas, named “ao” in Japanese or “q¯ing” in Chinese. It is used for the (green) traffic light (“ao shingo”) or the colour of unripe bananas, but also for a blue sky (“aozora”). The Berinmo, a Papua New Guinea indigineous culture, has a word “wor” which covers some of the green region, a word “nol” which covers much of green, blue and blue/purple, a word “wap” which covers almost all the lightest colours, and a word “kel” which covers almost all dark colours [7]. (3) Interestingly, a kind of switch has often happened or is happening in predominantly brightness-oriented colour languages towards predominantly fullcolour oriented languages which use both brightness and hue [8], showing that
there is not only evolution in how a strategy is instantiated (in other words which words and categories are used) but also which strategies a language community employs. Today’s hues like “yellow”, “brown”, or “blue” were all expressing brightness-based distinctions in Old English before they became used as part of the Basic Colour Strategy in the late Middle English period (1350-1500) [9], showing that the same linguistic elements (e.g. the same words) may be used by different strategies leading to a kind of competition and mutual influence across strategies. Given that we see variation and evolution at these two levels, we must conclude that individual language users master both language strategies, which are procedures for building, expanding, and adapting form-meaning mappings in order to achieve a particular communicative goal, and language systems, which are the concrete instantiations with respect to meanings (ontology), words (lexicon) or grammatical constructions (grammar) given a particular strategy. The communal language strategies, i.e. the strategies shared by all or most members of a population, and the communal language system, being the shared choices in a particular community, emerge out of the collective activity of all individuals and is not explicitly accessible nor represented. The goal of this paper is to understand and model the competition, selection and evolution of language strategies using colour as a concrete case study, specifically the interaction between brightness-based and full-colour-based strategies as attested in the evolution of English and many other languages.
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Language Strategies
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The first step in the investigation is to operationalise the language strategies themselves. We have done this here for two strategies: the Basic Colour Strategy and the Brightness Colour Strategy. We have chosen the U CIE L*u*v* space because the distance between two colours in this space accurately represents the psychological distances between these colours perceived -100 -50 0 50 100 by human subjects [10]. The L* dimension represents V brightness (ranging from black to white), the u* dimension represents the red-green opponent channel Fig. 2. A twoand the v* dimension the yellow-blue channel. A two- dimensional projection dimensional projection of the Munsell chips is shown of the Munsell chips on in Fig. 2. Colour categories are represented by a single the hue plane. A subset point in this colour space, usually called its focal pro- of these chips is used as totype [11], and categorisation can be modeled with the stimuli in a language a standard one-nearest neighbour classification algo- game. rithm. The prototypes nearest to each chip in the context are computed and categorisation is successful if there is a unique distinctive prototype found for the topic. This prototype is named and if this lead to a successful game, it is shifted with a very small factor towards the stimulus topic. When there is
another stimulus with the same prototype as the topic, a new prototype is introduced using the topic as seed. This happens at a very low rate, to ensure that new categories and the names to express them become sufficiently shared in the population before another new category is invented. When the hearer encounters a name he has never heard before, he adds a new association between this name and a newly created colour category based on the current topic. The Basic Colour Strategy uses all three dimensions of the colour space (both the brightness and the hue dimensions). Figure 3(a) shows that this strategy enables a population of agents to self-organize a colour lexicon from scratch. Figures 3(b) and 3(c) show the evolution of a colour lexicon in a typical experiment. 60
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Fig. 3. The Basic Colour Strategy allows a population of agents (in this case 10) to self-organise a colour lexicon from scratch (a). The graph shows how steady high communicative success is reached with a lexicon of about 15 colour words. The evolution of a typical lexicon in a smaller population (5 agents), is shown after 400 (b) and 1200 (c) games per agent. Each row represents the lexicon of one agent.
The Brightness Prototype Strategy is similar to the previous strategy, but instead of taking all three dimensions into account, only the L* dimension of both the stimuli in the context and the prototypes of the colour categories are compared. While learning, the prototype of the used colour category is shifted on the L* axis towards the L* value of the topic. During invention, only the L* value of the topic is considered relevant. Figure 4(a) shows that this strategy is also adequate to allow a population of agents to self-organize and coordinate a colour lexicon from scratch. The resulting colour lexicon now consists of different shades of gray (see Figs. 4(b) and 4(c) for the evolution of a typical lexicon).
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Strategy Selection
We can now turn to the main topic of this paper: how can there be selection and cooperation between different language strategies, and how can there be
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Fig. 4. The Brightness Colour Strategy also allows a population of agents (in this case 10) to evolve an adequate colour lexicon (a). The evolution of a typical lexicon in a smaller population (5 agents), is shown after 400 (b) and 1600 (c) games per agent. Each row represents the lexicon of one agent.
evolution, in the sense that one strategy overtakes another. Different strategies may cooperate in the sense that one strategy may be better in certain circumstances than in others. For example, a brightness colour vocabulary is obviously more appropriate when talking about black-and-white photographs. But strategies also compete because a population will obviously be more successful if each language user adopts the same default strategy for dealing with the same sort of communicative problem. There is also competition for words and meanings among the different strategies. A hearer cannot know whether a particular word (e.g. “yellow”) is to be interpreted using one strategy (brightness-based) or another one (full-colour-based), particularly because both strategies could work in similar circumstances. For example, yellow colour chips are often the most bright ones and hence both strategies would work. We have operationalised the linguistic selection of strategies in the following way. Each strategy is reified, in the sense that it is an object represented as such in the memory of the agents. A strategy has a score which reflects its ‘fitness’. This fitness is based on the communicative success of the words and meanings that were built or used with this strategy. The meanings, words or grammatical constructions are tagged with the strategy that has been used to invent or learn them. For example, if a word “dark” is acquired with the brightness-based strategy, it is tagged with that strategy. The same word may be tagged with different strategies because a learning agent does not know which strategy has been used by the speaker with a particular word and hence may have to make different hypotheses. In speaking, agents handle a communicative problem with the solution stored in their language system that had most success in the past and this solution implies a particular strategy. When the problem cannot be handled, the speaker has to expand his set of meanings and his lexicon and he prefers the default strategy, i.e. the strategy that had most success in the past. It is only when this strategy does not work that other alternative strategies are
tried out in decreasing order of fitness. In listening, the hearer first applies his own stored solution to interpret the utterance, which again implies the use of the language strategy associated with this solution. When the hearer is confronted with an unknown word or with a situation in which his interpretation of the word does not work for the present context (because apparently the speaker used another strategy for the word), he uses first his own default strategy to figure out the meaning of the unknown word, and, if that does not work, he tries out alternative strategies, again in the order of decreasing fitness. Due to space limitations, we can only show the outcome of one of our experiments to study the rich and complex dynamics that result from these behaviours. In this experiment, the set of prototypes is kept fixed, namely equal to the focal colours underlying the Spanish colour system [12]. However we left it open which strategy agents should use. For example, the word “morado” (purple) can both be interpreted in the full-colour space and in the brightness space. Two situations arise. In one situation, a single strategy becomes clearly dominant in the population. This could either be the brightness or the full colour strategy, depending on small fluctuations in the early stages (Fig. 5(a)). But we have also observed situations where one strategy becomes dominant first (for example, the brightness strategy) to be overtaken later by another strategy (i.c. the full-colour strategy), as seen in the history of English (Fig. 5(b)). The two strategies continue to co-exist in this case. Brightness is still used in circumstances where this gives a higher chance of communicative success, for example when colour chips are close in hue but distinct in brightness or when there is a word which has most of its success in the brightness dimension.
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Conclusion
Language strategies can only compete with each other through the use of the language systems that they enable their users to build. And language systems can only be tested through the production and comprehension of concrete utterances. So we get selection at two levels: (1) The application of a language strategy by a population generates possible variation (possible categories, possible words) and those variants that lead to higher communicative success undergo positive selection and are hence re-used in future communications. We have shown that this selectionist process can be orchestrated by coupling communicative success to language adaptation (Figs. 3(a) and 4(a)). (2) The recruitment of cognitive functions generates possible language strategies and those strategies that lead to the construction of language systems with higher communicative success undergo positive selection, and are thus used even more in the future. We have shown here that this selectionist process can be orchestrated by having the agents keep track of which strategy they used for the building and interpretation of a particular word as well as the long term communicative success of each strategy (its fitness). We have shown that this dynamics allows a population to settle on a dominant default strategy although there is not necessarily a winner-take-all situation (Figs. 5(a) and 5(b)).
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(b) Fig. 5. In (a) the Brightness Colour Strategy becomes entirely dominant and is used significantly more, whereas in (b) one strategy overtakes the dominant one which is reflected in the respective use of each strategy.
The same sort of competition and selection between different strategies has been observed in many areas of lexical and grammatical evolution. For example, there is currently an evolution going on in Spanish clitics (“le”, “la”, “lo”) whereby the etymological system of Standard Spanish, which uses clitics to express different cases (nominative, dative, accusative), is shifting to a referential system in which case differentiation is lost, but with existing forms recruited for
expressing gender and number distinctions [13]. The two-level selectionist dynamics discussed here is relevant to understand more broadly how an individual may select the language strategies used in his or her language community and how language strategies may evolve in the historical evolution of a language.
Acknowledgements This research is funded through a fellowship of the Institute of the Promotion of Innovation through Science and Technology in Flanders (IWT-Vlaanderen), with additional funding from the EU FP7 ALEAR project and the Sony Computer Science Laboratory in Paris.
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