``L'homme et la société embêtent la philosophie ...' Bocheński on the limits of `philosophy'

Following his retirement fromUniversity teaching in 1972 Bocheski focusedincreasingly on metaphilosophical issues. Someof these he considered in occasional papers,autobiographical essays, as well as interviews,often giving expression to views that are asrefreshing as they are – sometimes –surprising. Bocheski in his later years becamesomething of an iconoclast, sharply criticalof, indeed hostile to, much of what isparadigmatically taken to be `philosophy'. Inthis paper, I draw out and examine some aspectsof Bocheski's virtually anti-philosophicalattitudes and try my hand at an analysis ofwhat appears to have become the Bocheski'smain underlying motivation in this respect: theless than happy interplay of religious faith,Weltanschauungen, and philosophy caughtbetween two seemingly persistent butconflicting inclinations of the human spirit tosubmit to the authority of some `total' picture.     

Semantic interpretation as computation in nonmonotonic logic: the real meaning of the suppression task

Interpretation is the process whereby a hearer reasons to an interpretation of a speaker's discourse. The hearer normally adopts a credulous attitude to the discourse, at least for the purposes of interpreting it. That is to say the hearer tries to accommodate the truth of all the speaker's utterances in deriving an intended model. We present a nonmonotonic logical model of this process which defines unique minimal preferred models and efficiently simulates a kind of closed-world reasoning of particular interest for human cognition. Byrne's "suppression" data (Byrne, 1989) are used to illustrate how variants on this logic can capture and motivate subtly different interpretative stances which different subjects adopt, thus indicating where more fine-grained empirical data are required to understand what subjects are doing in this task. We then show that this logical competence model can be implemented in spreading activation network models. A one pass process interprets the textual input by constructing a network which then computes minimal preferred models for (3-valued) valuations of the set of propositions of the text. The neural implementation distinguishes easy forward reasoning from more complex backward reasoning in a way that may be useful in explaining directionality in human reasoning.