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Rivelli, Luca (2015) Modularity, Antimodularity and Explanation in Complex Systems. [Tesi di dottorato]

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Abstract (inglese)

This work is mainly concerned with the notion of hierarchical modularity and its use in explaining structure and dynamical behavior of complex systems by means of hierarchical modular models, as well as with a concept of my proposal, antimodularity, tied to the possibility of the algorithmic detection of hierarchical modularity. Specifically, I highlight the pragmatic bearing of hierarchical modularity on the possibility of scientific explanation of complex systems, that is, systems which, according to a chosen basic description, can be considered as composed of elementary, discrete, interrelated parts. I stress that hierarchical modularity is also required by the experimentation aimed to discover the structure of such systems. Algorithmic detection of hierarchical modularity turns out to be a task plagued by the demonstrated computational intractability of the search for the best hierarchical modular description, and by high computational expensiveness of even approximated detection methods. Antimodularity consists in the lack of a modular description fitting the needs of the observer, due either to absence of modularity in the system's chosen basic description, or to the impossibility, due to the excessive size of the system under assessment in relation to the computational cost of algorithmic methods, to algorithmically produce a valid hierarchical description. I stress that modularity and antimodularity depend on the pragmatic choice of a given basic description of the system, a choice made by the observer based on explanatory goals. I show how antimodularity hinders the possibility of applying at least three well-known types of explanation: mechanistic, deductive-nomological and computational. A forth type, topological explanation, remains unaffected. I then assess the presence of modularity in biological systems, and evaluate the possible consequences, and the likeliness, of incurring in antimodularity in biology and neuroscience, concluding that this eventuality is quite likely, at least in systems biology. I finally indulge in some metaphysical and historical speculation: metaphysically, antimodularity seems to suggest a possible position according to which natural kinds are detected modules, and as such, due to computational hardness of the detection of the best hierarchical modular description, they are unlikely to be the best possible way to describe the world, because the modularity of natural kinds quite probably does not reflect the best possible modularity of the world. From an historical point of view, the growing use of computational methods for modularity detection or simulation of complex systems, especially in certain areas of scientific research, hints to the envisioning of a multiplicity of emerging scientific disciplines guided by a self-sustained, growing production of possibly human-unintelligible explanations. This, I suggest, would constitute an historical change in science, which, if has not already happened, could well be on the verge of happening.

Abstract (italiano)

Questo lavoro riguarda principalmente il concetto di modularità gerarchica e il suo impiego nello spiegare la struttura e il comportamento dinamico di sistemi complessi mediante modelli modulari gerarchici, nonché un concetto di mia proposta, l'antimodularità, legato alla possibilità di rilevamento algoritmico di modularità gerarchica. Nello specifico, evidenzio la portata pragmatica della modularità gerarchica sulla possibilità di spiegazione scientifica dei sistemi complessi, cioè sistemi che, secondo una descrizione di base scelta dall'osservatore, possono essere considerati come composti da parti elementari discrete interrelate. Sottolineo che la modularità gerarchica è essenziale anche nel corso della sperimentazione volta a scoprire la struttura di tali sistemi. Il rilevamento algoritmico della modularità gerarchica si rivela essere un compito affetto dalla dimostrata intrattabilità computazionale della ricerca della migliore descrizione modulare gerarchica, e affetto dal comunque elevato costo computazionale anche dei metodi di rilevamento approssimati. L'antimodularità consiste nella mancanza di una descrizione modulare adatta alle esigenze dell'osservatore, dovuta o all'assenza di modularità nella descrizione di base del sistema scelta dall'osservatore, o all'impossibilità di produrre algoritmicamente una descrizione gerarchica valida, per le dimensioni eccessive del sistema da valutare in rapporto al costo computazionale dei metodi algoritmici. Sottolineo che modularità e antimodularità dipendono dalla scelta pragmatica di una certa descrizione di base del sistema, scelta fatta dall'osservatore sulla base di obiettivi esplicativi. Mostro poi come l'antimodularità ostacoli la possibilità di applicare almeno tre tipi noti di spiegazione: meccanicistica, deduttivo-nomologica e computazionale. Un quarto tipo di spiegazione, la spiegazione topologica, rimane sostanzialmente immune dalle conseguenze dell'antimodulairità. Valuto quindi la presenza di modularità nei sistemi biologici, e le possibili conseguenze, nonché l'eventualità di incorrere nell'antimodularità in biologia e nelle neuroscienze, concludendo che questa eventualità è abbastanza probabile, almeno in biologia dei sistemi. Infine, mi permetto qualche speculazione metafisica e storica. Dal punto di vista metafisico, l'antimodularità sembra suggerire una posizione possibile, secondo cui i generi naturali sono moduli che sono stati rilevati, e in quanto tali, a causa dell'intrattabilità computazionale del rilevamento della migliore descrizione modulare gerarchica, è improbabile che essi siano il miglior modo possibile per descrivere il mondo, perché la modularità dei generi naturali molto probabilmente non rispecchia la migliore modularità possibile del mondo. Da un punto di vista storico, il crescente utilizzo di metodi computazionali per il rilevamento della modularità o per la simulazione di sistemi complessi, in particolare in alcuni settori della ricerca scientifica, suggerisce la possibilità di immaginare una molteplicità di discipline scientifiche emergenti, guidate dalla produzione di spiegazioni potenzialmente inintelligibili dal punto di vista cognitivo umano, produzione che potrebbe iniziare ad autoalimentarsi, portando potenzialmente ad una crescita inarrestabile. Suggerisco che questo scenario costituirebbe un cambiamento epocale nel campo della scienza, che, se non è già avvenuto, potrebbe benissimo essere sul punto di realizzarsi.

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Tipo di EPrint:Tesi di dottorato
Relatore:Grigenti, Fabio
Correlatore:Huneman, Philippe
Dottorato (corsi e scuole):Ciclo 26 > Scuole 26 > FILOSOFIA
Data di deposito della tesi:31 Luglio 2015
Anno di Pubblicazione:30 Luglio 2015
Informazioni aggiuntive:Tesi in cotutela con l'IHPST - Université Paris 1 Panthéon-Sorbonne
Parole chiave (italiano / inglese):Modularità, Modularity, Explanation, computation, spiegazione scientifica,computazione, emergence, philosophy of biology, philosophy of science
Settori scientifico-disciplinari MIUR:Area 11 - Scienze storiche, filosofiche, pedagogiche e psicologiche > M-STO/05 Storia della scienza e delle tecniche
Area 11 - Scienze storiche, filosofiche, pedagogiche e psicologiche > M-FIL/02 Logica e filosofia della scienza
Area 11 - Scienze storiche, filosofiche, pedagogiche e psicologiche > M-FIL/06 Storia della filosofia
Struttura di riferimento:Dipartimenti > Dipartimento di Filosofia, Sociologia, Pedagogia e Psicologia Applicata
Codice ID:8926
Depositato il:29 Ago 2016 13:02
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