Darwin’s first two, relatively complete, explicit articulations of his theorizing on evolution were his Essay of 1844 and On the Origin of Species published in 1859. A comparative analysis concludes that they espoused radically different theories despite exhibiting a continuity of strategy, much common structure and the same key idea. Both were theories of evolution by means of natural selection. In 1844, organic adaptation was confined to occasional intervals initiated and controlled by de-stabilization events. The modified descendants rebalanced the particular (...) “plant and animal forms … unsettled by some alteration in their circumstances.” But by 1859, organic adaptation occurred continuously, potentially modifying the descendants of all organisms. Even natural selection, the persistent core of Darwin’s theorizing, does not prove to be a significant basis for theory similarity. Consequently, Darwin’s Origin theory cannot reasonably be considered as a mature version of the Essay. It is not a modification based on adjustments, further justifications and the integration of a Principle of Divergence. The Origin announced a new “scientific paradigm” while the Essay did little more than seemingly misconfigure the operation of a novel mechanism to extend varieties beyond their accepted bounds, and into the realm of possible new species. Two other collections of Darwin’s theorizing are briefly considered: his extensive notes of the late 1830s and his contributions to the famous meeting of 1 July 1858. For very different reasons, neither constitutes a challenge to the basis for this comparative study. It is concluded that, in addition to the much-debated social pressures, an unacknowledged further reason why Darwin did not publish his theorizing until 1859, could have been down to his perceptive technical judgement: wisely, he held back from rushing to publish demonstrably flawed theorizing. (shrink)

This outstanding collection is designed to address the fundamental issues and principles underlying the task of Artificial Intelligence.

In this paper I shall describe the symbolic search space paradigm which is the dominant model for most of AI. Coupled with the mechanisms of logic it yields the predominant methodology underlying expert systems which are the most successful application of AI technology to date. Human decision making, more precisely, expert human decision making is the function that expert systems aspire to emulate, if not surpass.Expert systems technology has not yet proved to be a decisive success — it appears to (...) fare better in some areas of human expertise than others. As a result subdomains of human expertise are variously categorised and we shall examine a few of the suggested classification schemes. A particular line of argument explored is one which maintains that certain types of human decision making, at least, are not adequately approximated by the symbolic search space paradigm of AI. Furthermore, attempts to project this inadequate model of human decision making via implementations of expert systems will be detrimental to both our image of ourselves and the future possibilities for AI software.Finally, we examine one possible route to the realization of AI, perhaps even practical applications of AI, that is a significant alternative to the model offered by the symbolic search space paradigm. (shrink)

Language sciences have long maintained a close and supposedly necessary coupling between the infinite productivity of the human language faculty and recursive grammars. Because of the formal equivalence between recursion and non-recursive iteration; recursion, in the technical sense, is never a necessary component of a generative grammar. Contrary to some assertions this equivalence extends to both center-embedded relative clauses and hierarchical parse trees. Inspection of language usage suggests that recursive rule components in fact contribute very little, and likely nothing significant, (...) to linguistic creativity. Further than this, if the productivity of human language is considered as not rigidly bound, but not infinite, then the need for any sort of iteration in generative grammars vanishes and can be replaced with a Non-iterative Explicit Alternatives Rule grammar. The knock-on effects of dispensing with recursive grammar components are: that language diversity can simply be based on rule and lexicon combinatorics with no potentially infinite dimensions derived from recursive or iterative components of rules; the oddity of a vast, multiply-infinite competence set of ‘grammatical but unacceptable’ productions is gone; and the development of a language faculty based on rules that eschew iterative rule components avoids any need for explaining ‘special’ mechanisms. On the broader front of searching for the mechanisms of mind, our analysis can be similarly applied to the proposals for a recursive basis for mind as an explanation for humanity’s great leap forward. (shrink)

This paper argues that Information Theoretic Redundancy (ITR) is fundamentally a composite concept that has been continually misinterpreted since the very inception of Information Theory. We view ITR as compounded of true redundancy and partial redundancy. This demarcation of true redundancy illustrates a limiting case phenomenon: the underlying metric (number of alternatives) differs only by degree but the properties of this concept differ in kind from those of partial redundancy. Several other studies are instanced which also imply the composite nature (...) of ITR. We thus provide broadly based but particular support for earlier generalized suggestions that it is the underlying calculus of Information Theory rather than the ill-named concepts themselves that provides something of a unitary language for the description of phenomena. (shrink)

The fundamental assumptions in Dijkstra''s influential article on computing science teaching are challenged. Dijkstra''s paper presents the radical novelties of computing, and the consequent problems that we must tackle through a formal, logic-based approach to program derivation. Dijkstra''s main premise is that the algorithmic programming paradigm is the only one, in fact, the only possible one. It is argued that there is at least one other, the network-programming paradigm, which itself is a radical novelty with respect to the implementation of (...) problems on computers. And, as one might expect of a radical alternative, it shows much of the conventional wisdom concerning computing science, which Dijkstra variously attacks and dispenses, to be special pleading; not universals of computing at all. Finally, we explore what is known of this new paradigm in order to see what light it sheds on the fundamental problems that computing really does present to us. Not surprisingly, some become less problematic, some disappear altogether and others take their place, but, in general, it must be of benefit to modern computer technology to gain a wider perspective on the possibilities instead of seeing everything through the traditional tunnel of programming as formula derivation, and computers as the requisite, special type of symbol manipulation device. (shrink)

The notion of specification plays a key role in the developing science of computing. It is typically considered to be the keystone in the software development process. However, there is no single, generally agreed meaning of specification that bears close scrutiny. Instead there is a variety of different, although partially interlocking and overlapping interpretations of the term.We catalogue this varietal profusion and attempt to lay bare both the sources and consequences of each major alternative. We attempt to present the full (...) range of possibilities, and the biases inherent in each style of interpretation. (shrink)