Schemata

No abstract available

Learning-based constraints on schemata

Schemata are frequently used in cognitive science as a descriptive framework for explaining the units of knowledge. However, the specific properties which comprise a schema are not consistent across authors. In this paper we attempt to ground the concept of a schema based on constraints arising from issues of learning. To do this, we consider the different forms of schemata used in computational models of learning. We propose a framework for comparing forms of schemata which is based on the underlying representation used by each model, and the mechanisms used for learning and retrieving information from its memory. Based on these three characteristics, we compare examples from three classes of model, identified by their underlying representations, specifically: neural network, production-rule and symbolic network models

Automated software development workstation

Engineering software development was automated using an expert system (rule-based) approach. The use of this technology offers benefits not available from current software development and maintenance methodologies. A workstation was built with a library or program data base with methods for browsing the designs stored; a system for graphical specification of designs including a capability for hierarchical refinement and definition in a graphical design system; and an automated code generation capability in FORTRAN. The workstation was then used in a demonstration with examples from an attitude control subsystem design for the space station. Documentation and recommendations are presented

The Semantics of Graph Programs

GP (for Graph Programs) is a rule-based, nondeterministic programming language for solving graph problems at a high level of abstraction, freeing programmers from handling low-level data structures. The core of GP consists of four constructs: single-step application of a set of conditional graph-transformation rules, sequential composition, branching and iteration. We present a formal semantics for GP in the style of structural operational semantics. A special feature of our semantics is the use of finitely failing programs to define GP's powerful branching and iteration commands

Short papers and letters on the 'linear micro-element' theory of mental mechanism; and related questions of scientific method

Seven papers/letters further developing the ideas raised in Monographs #12 and #15 (q.v.), and in two papers published in Kybernetes (vols 5 and 7) -- later incorporated into the Thesis (q.v.) as "Part A". In particular: *Chapters I & VI: apply the postulated 'linear elements' to explain Piaget's notion of how the mental concept of 'object' is developed. *Chapter II: extends this to account for the rudiments of 'personal identity'. *Chapter III: answers criticisms and queries raised by Dr N.E.Wetherick, mainly on the plausibility of RNA and infra-red as a Second (multiplexed) Neurotransmitting System. *Other chapters offer critiques of some accepted views on scientific method