Steps Toward the Synthetic Method: Symbolic Information Processing and Self-Organizing Systems in Early Artificial Intelligence Modeling

Abstract

All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from the publisher.

The Problem of Prediction in Artificial Intelligence and Synthetic Biology

“…In other terms, we want to predict the running of the program in the best possible way. The halting problem is a logical obstacle to this requirement for the programs, a hard one as regards prediction; (b) prediction is important for game theory and decision theory, whose aims are, among others, to predict the agent's behavior in an interactive situation or in a choice situation, and where one of the crucial notions is that of expected utility; (c) prediction is significant in the simulative approach in the science of the artificial, and with reference to the synthetic method (see [15]), to build and exploit software and/or hardware models and artifacts with a rational/intelligent/cognitive behavior. The way in which we build the model, or the artifact as a model, includes elements the builder thinks the model should have to show a specific behavior, which of course could also be disregarded in the case of a wrong prediction; and (d) prediction is important in understanding future technological developments and their impacts.…”

“…Evolutionary techniques in SB engineering are useful for in vitro experiments, but in general, SB does not like overwhelmingly emergent phenomena [41], because it is hard to control SB products if their properties, development and behavior are emergent, especially when SB products have to be inserted in the real world. To study emergent entities, behaviors and products of evolutionary processes, AI uses computer simulation and models, especially in the framework of the synthetic method [15]. The test bench of synthetic method outcomes, however, is often (e.g., in robotics) the interaction with the real world.…”

Natural and Artificial Systems: Compare, Model or Engineer?

“…The degree to which 'the hypothesis accounts for existing data and predicts new data from observations on the target phenomenon is taken to support its status as an explanation' [7]. Cordeschi explains further: 'The artefact therefore embodies the explanatory principles (the hypotheses) of the theory and is considered a test of the theory's plausibility' [10]. 4 However, the hypothesis is only associated with a simplified or narrow element of the natural system, factoring out unrelated phenomena, to make analysis possible [10].…”

“…It is in this spirit that we include clarification of how the developing fields of bioengineering relate to the epistemological approaches of comparison and modeling. Finally, following Cordeschi [10] our intention here is not to carve unnecessary boundaries between approaches and opposing paradigms (i.e. we think that both comparative and modeling work is important, and within them, work from different kinds of theoretical positions).…”

Large-scale simulations of brain mechanisms: beyond the synthetic method

“…Otherwise, one may be induced to reject that hypothesis. Under a variety of epistemological and methodological assumptions, whose analysis is out of the scope of this contribution (see Cordeschi, 2002Cordeschi, , 2008Webb, 2006;Datteri and Tamburrini, 2007;Datteri, 2016), the synthetic method may therefore assist one in identifying the mechanism underlying a particular (observed) behaviour. This may be called a model-oriented use of simulations.…”