Jean-Louis Dessalles

Algorithmic Simplicity and Relevance

The human mind is known to be sensitive to complexity. For instance, the visual system reconstructs hidden parts of objects following a principle of maximum simplicity. We suggest here that higher cognitive processes, such as the selection of relevant situations, are sensitive to variations of complexity. Situations are relevant to human beings when they appear simpler to describe than to generate. This definition offers a predictive (i.e. falsifiable) model for the selection of situations worth reporting (interestingness) and for what individuals consider an appropriate move in conversation.

Storing events to retell them

Episodic memory is certainly a unique endowment, but its primary purpose is something other than to provide raw material for creative synthesis of future scenarios. Remembered episodes are exactly those which are worth telling. The function of episodic memory, in our view, is to accumulate stories that are relevant to recount in conversation.

Can believable characters act unexpectedly

Unexpectedness is a major factor controlling interest in narratives. Emotions, for instance, are felt intensely if they are associated with unexpected events. The problem with generating unexpected situations is that either characters, or the whole story, are at risk of being no longer believable. This issue is one of the main problems that make story design a hard task. Writers face it on a case by case basis. The automatic generation of interesting stories requires formal criteria to decide to what extent a given situation is unexpected and to what extent actions are kept believable. This paper proposes such formal criteria and makes suggestions concerning their use in story generation systems. 1. The unexpectedness-believability dilemma Interest in narratives crucially relies on the author’s ability to design unexpected situations. The exercise requires however a bit of caution, as the following example illustrates. The Knife Story. John and Mary are true lovers. Over time, their love is growing. On that Tuesday, Mary has breakfast with John as usual. She stands up, goes to the kitchen, grabs a knife, returns and stabs John in the back. This example illustrates the mutual exclusion between unexpectedness and believability. Mary’s action does not make sense at this point of the story. Readers are in a desperate need for an explanation that will restore Mary’s rationality. In the absence of such explanation, or if it comes too late, Mary’s character is at risk of appearing non believable, and the story’s attractiveness will suffer as a result. Few authors addressed the issue on a general basis. The narrative generator Prevoyant (Bae and Young, 2008) is an attempt to generate flashback and foreshadowing, specifically targeted at the evocation of surprise in the reader’s mind. Surprise is mainly aroused by the manipulation of temporal structures in the narrative. Foreshadowing provides the reader with expectations and flashback provides the reader with an explanation of the surprising event. Using a reader model, the system evaluates both the presence of an unexpected event and the fact that the story structure as a whole will hang together and make sense to the reader. Suspenser (Cheong and Young, 2008) is a framework that determines narrative contents intended to arouse high level of suspense in the reader. This system relies on the idea that a reader’s suspense level is affected by the problems that characters must face and by the number of solutions available to them. The system manipulates the story events in order to increase or decrease the chances of success and also proposes a measure of the level of suspense. Both studies, Prevoyant and Suspenser, address the question of generating coherent stories that arouse an effect in the reader. However, the problem of creating interesting situations by generating surprise or suspense is addressed considering only some specific aspect of these notions. No general theoretical framework that would serve as guidance for the generation of interesting and believable narratives is provided.Reconciling unexpectedness and believability is generally considered as a skill that often makes the difference between good and average quality fiction. The automatic generation of interesting stories requires some formal criterion to decide to what extent a given situation is unexpected and whether actions are kept believable. The aim of this paper is to offer such a formal criterion and to show how it could be implemented in story generation systems. In what follows, we will first illustrate with an example (the Grail Story) how unexpectedness is used by authors to raise interest. They often bring characters to the frontiers of believability. To reproduce this skill, a theoretical framework is needed. We consider such a framework, Simplicity Theory, in a further section. After a brief presentation of the theory, we will show how it can be used to formally characterize two notions: surprise and intentionality. Thanks to these definitions, we will be able not only to express the unexpectedness-believability dilemma, but also to get around it. We will then go further, showing how the theoretical definitions can lead to practical calculus and, eventually, could be used in story generation systems.

OPTIMAL INVESTMENT IN SOCIAL SIGNALS

This study is an attempt to determine how much individuals should invest in social communication, depending on the type of relationships they may form. Two simple models of social relationships are considered. In both models, individuals emit costly signals to advertise their “quality” as potential friends. Relationships are asymmetrical or symmetrical. In the asymmetrical condition (first model), we observe that low‐quality individuals are discouraged from signaling. In the symmetrical condition (second model), all individuals invest in communication. In both models, high‐quality individuals (elite) do not compete and signal uniformly. The level of this uniform signal and the size of the “elite” turn out to be controlled by the accuracy of signals. The two models may be relevant to several aspects of animal and human social communication.

Reasoning as a lie detection device

The biological function of human reasoning abilities cannot be to improve shared knowledge. This is at best a side effect. A more plausible function of argumentation, and thus of reasoning, is to advertise ones ability to detect lies and errors. Such selfish behavior is closer to what we should expect from a naturally selected competence.

Sharing cognitive dissonance as a way to reach social harmony

Commonsense wisdom dictates that mutual understanding grows with cognitive harmony. Communication seems impossible between people who do not share values, beliefs and concerns. If carried to the extreme, however, this statement neglects the fact that the formation of social bonds crucially depends on the expression of cognitive dissonance.

Spontaneous narrative behaviour in homo sapiens: how does it benefit to speakers?

The fact that human beings universally put much energy and conviction in reporting events in daily conversations demands an explanation. After having observed that the selection of reportable events is based on unexpectedness and emotion, we make a few suggestions to show how the existence of narrative behaviour can be consistent with the socio-political theory of the origin of language.

From Conceptual Spaces to Predicates

Why is a red face not really red? How do we decide that this book is a textbook or not? Conceptual spaces provide the medium on which these computations are performed, but an additional operation is needed: Contrast. By contrasting a reddish face with a prototypical face, one gets a prototypical ‘red’. By contrasting this book with a prototypical textbook, the lack of exercises may pop out. Dynamic contrasting is an essential operation for converting perceptions into predicates. The existence of dynamic contrasting may contribute to explaining why lexical meanings correspond to convex regions of conceptual spaces. But it also explains why predication is most of the time opportunistic, depending on context. While off-line conceptual similarity is a holistic operation, the contrast operation provides a context-dependent distance that creates ephemeral predicative judgments (‘this book is not a textbook’, ‘this author is a linguist’) that are essential for interfacing conceptual spaces with natural language and with reasoning.

A Cognitive Approach to Relevant Argument Generation

Acceptable arguments must be logically relevant. This paper describes an attempt to retro-engineer the human argumentative competence. The aim is to produce a minimal cognitive procedure that generates logically relevant arguments at the right time. Such a procedure is proposed as a proof of principle. It relies on a very small number of operations that are systematically performed: logical conflict detection, abduction and negation. Its eventual validation however depends on the quality of the available domain knowledge.

Using Unexpected Simplicity to Control Moral Judgments and Interest in Narratives.

The challenge of narrative automatic generation is to produce not only coherent, but interesting stories. This study considers the problem within the Simplicity Theory framework. According to this theory, interesting situations must be unexpectedly simple, either because they should have required complex circumstances to be produced, or because they are abnormally simple, as in coincidences. Here we consider the special case of narratives in which characters perform actions with emotional consequences. We show, using the simplicity framework, how notions such as intentions, believability, responsibility and moral judgments are linked to narrative interest.