Driven by Compression Progress: A Simple Principle Explains Essential Aspects of Subjective Beauty, Novelty, Surprise, Interestingness, Attention, Curiosity, Creativity, Art, Science, Music, Jokes

I argue that data becomes temporarily interesting by itself to some self-improving, but computationally limited, subjective observer once he learns to predict or compress the data in a better way, thus making it subjectively simpler and more beautiful. Curiosity is the desire to create or discover more non-random, non-arbitrary, regular data that is novel and surprising not in the traditional sense of Boltzmann and Shannon but in the sense that it allows for compression progress because its regularity was not yet known. This drive maximizes interestingness, the first derivative of subjective beauty or compressibility, that is, the steepness of the learning curve. It motivates exploring infants, pure mathematicians, composers, artists, dancers, comedians, yourself, and (since 1990) artificial systems.Comment: 35 pages, 3 figures, based on KES 2008 keynote and ALT 2007 / DS 2007 joint invited lectur

Ultimate Cognition à la Gödel

"All life is problem solving,” said Popper. To deal with arbitrary problems in arbitrary environments, an ultimate cognitive agent should use its limited hardware in the "best” and "most efficient” possible way. Can we formally nail down this informal statement, and derive a mathematically rigorous blueprint of ultimate cognition? Yes, we can, using Kurt Gödel's celebrated self-reference trick of 1931 in a new way. Gödel exhibited the limits of mathematics and computation by creating a formula that speaks about itself, claiming to be unprovable by an algorithmic theorem prover: either the formula is true but unprovable, or math itself is flawed in an algorithmic sense. Here we describe an agent-controlling program that speaks about itself, ready to rewrite itself in arbitrary fashion once it has found a proof that the rewrite is useful according to a user-defined utility function. Any such a rewrite is necessarily globally optimal—no local maxima!—since this proof necessarily must have demonstrated the uselessness of continuing the proof search for even better rewrites. Our self-referential program will optimally speed up its proof searcher and other program parts, but only if the speed up's utility is indeed provable—even ultimate cognition has limits of the Gödelian kin

Minimal requirements for the cultural evolution of language

Human language is both a cognitive and a cultural phenomenon. Any evolutionary account of language, then, must address both biological and cultural evolution. In this thesis, I give a mainly cultural evolutionary answer to two main questions: firstly, how do working systems of learned communication arise in populations in the absence of external or internal guidance? Secondly, how do those communication systems take on the fundamental structural properties found in human languages, i.e. systematicity at both a meaningless and meaningful level? A large, multi-disciplinary literature exists for each question, full of apparently conflicting results and analyses. My aim in this thesis is to survey this work, so as to find any commonalities and bring this together in order to provide a minimal account of the cultural evolution of language. The first chapter of this thesis takes a number of well-established models of the emergence of signalling systems. These are taken from several different fields: evolutionary linguistics, evolutionary game theory, philosophy, artificial life, and cognitive science. By using a common framework to directly compare these models, I show that three underlying commonalities determine the ability of any population of agents to reliably develop optimal signalling. The three requirements are that i) agents can create and transfer referential information, ii) there is a systemic bias against ambiguity, and iii) some mechanism leading to information loss exists. Following this, I extend the model to determine the effects of including referential uncertainty. I show that, for the group of models to which this applies, this places certain extra restrictions on the three requirements stated above. In the next chapter, I use an information-theoretic framework to construct a novel analysis of signalling games in general, and rephrase the three requirements in more formal terms. I then show that we can use these 3 criteria as a diagnostic for determining whether any given signalling game will lead to optimal signalling, without the requirement for repeated simulations. In the final, much longer, chapter, I address the topic of duality of patterning. This involves a lengthy review of the literature on duality of patterning, combinatoriality, and compositionality. I then argue that both levels of systematicity can be seen as a functional adaptation which maintains communicative accuracy in the face of noisy processes at different levels of analysis. I support this with results from a new, minimally-specified model, which also clarifies and informs a number of long-fought debates within the field

Towards Effective English Teaching

In view of the increasing need for learning English in a more and more demanding society, the present study aims to evaluate the effectiveness of the teaching of English in Spanish schools. The investigation has been carried out in four schools which follow two different teaching methodologies. This has enabled us to analyze how the use of a certain teaching methodology or strategy influences the communicative competence in English and the ease with which the language is spoken. The analysis of the data gathered has led us to the proposal of improvements to make the teaching of English more effective