Strukturalna teoria automatów skończonych określonych za pomocą matryc

Praca przedstawiona Radzie Wydziau Matematyki, Fizyki i Chemii Uniwersytetu Wrocawskiego w celu uzyskania stopnia doktora nauk matematycznych.Allatum est die 11 Aprilis 1964     

Analityczne komponenty definicji arbitralnych

Tre: Wstp. I. Definicje arbitralne. II. Syntetyczne konsekwencje definicji arbitralnych III. Analityczne i rzeczowe komponenty definicji arbitralnych. IV. Zdania analityczne.Artyku ten w nieznacznym tylko stopniu róni si od pracy doktorskiej, któr przedstawiem w 1962 r. Jak najuprzejmiej dzikuj Prof. Dr M. Kokoszyskiej-Lutman, Prof. Dr J. Supeckiemu oraz Doc. Dr M. Przeckiemu za szereg uwag i wskazówek, z których tak wiele skorzystaem przygotowujc ostateczn redakcj pracy.     

Constraints and Preferences in Inductive Learning: An Experimental Study of Human and Machine Performance

The paper examines constraints and preferences employed by people in learning decision rules from preclassified examples. Results from four experiments with human subjects were analyzed and compared with artificial intelligence (AI) inductive learning programs. The results showed the people's rule inductions tended to emphasize category validity (probability of some property, given a category) more than cue validity (probability that an entity is a member of a category given that it has some property) to a greater extent than did the AI programs. Although the relative proportions of different rule types (e.g., conjunctive vs. disjunctive) changed across experiments, a single process model provided a good account of the data from each study. These observations are used to argue for describing constraints in terms of processes embodied in models rather than in terms of products or outputs. Thus AI induction programs become candidate psychological process models and results from inductive learning experiments can suggest new algorithms. More generally, the results show that human inductive generalizations tend toward greater specificity than would be expected if conceptual simplicity were the key constraint on inductions. This bias toward specificity may be due to the fact that this criterion both maximizes inferences that may be drawn from category membership and protects rule induction systems from developing over-generalizations.     

The Logic of Plausible Reasoning: A Core Theory

The paper presents a core theory of human plausible reasoning based on analysis of people's answers to everyday questions about the world. The theory consists of three parts:

• 1 a formal representation of plausible inference patterns; such as deductions, inductions, and analogies, that are frequently employed in answering everyday questions;
• 2 a set of parameters, such as conditional likelihood, typicality, and similarity, that affect the certainty of people's answers to such questions; and
• 3 a system relating the different plausible inference patterns and the different certainty parameters.

This is one of the first attempts to construct a formal theory that addresses both the semantic and parametric aspects of the kind of everyday reasoning that pervades. all of human discourse.