The structure of an Intelligent Multiactuator System (IMS) is discussed which is determined as a system with redundancies, where the choice between concurring alternatives appears at a definite stage as a regular procedure of system operation. The structure of the IMS is considered as a product of four hierarchies: targets, memories, propensities, and impacts. The optimum behavior is determined by anthropomorphic heuristics at the levels of planning and navigation. The optimum control of subsystems is computed at the lowest level of intelligence. The structures of optimum control are recommended which imply the online performance only for a limited amount of procedures.

Intelligent control of a multiactuator system

Intelligent Control of a Multiactuator System

Previous axiomatic studies of the list structures of LISP by Moore and by Butrick have pointed out that the full system for list structures with recursion and an induction schema is incomplete(able). This paper develops a decision procedure for elementary list structures without recursion (List-S) which is complete. Every sentence of List-S is shown to be such that either it or its negation is a member (theorem) of List-S by the decision procedure.

A complete system generation algorithm for List structures

This paper (1) points out the inadequacies of the standard mathematical approach to n- tuples, (2) develops an axiomatic base for linear dyadic structures (list structures), (3) uses the axiomatic base to (a) prove a theorem which shows that the system requires an infinite model (Foundedness Theorem), (b) define n-tuples and (c) prove a theorem used in fast pattern matching (Fundamental N-tuple Theorem). Finally, (4) the system is shown to be consistent.

Daniel Hoskins

Papers

The foundations of the logic of N-tuples