CFP: Logic, Spatial Algorithms and Visual Reasoning (Special Issue of Logica Universalis)
Submission deadline: July 15, 2021
Logic, Spatial Algorithms and Visual Reasoning (Special Issue of Logica Universalis)
Andrew Schumann, Jens Lemanski (Editors)
How important spatial visualization ability is for us humans, we know from our everyday life as well as from all areas of science: We do not only move and orientate ourselves in space, but we also examine spatial objects with our logical abilities or use spatial relations to examine our logical abilities with them. This close connection of spatial and logical abilities is not only reflected in geometry, diagrammatic logic, but also in everyday metaphors, mental images and visualisations that we need to find our way in space or to use the space for our creative processes. We now know from fields such as cognitive sciences, animal learning, and evolutionary psychology that not only humans think in spatial relations, but animals in general. Furthermore, we also know that not only our understanding of animal intelligence, but also machine or artificial intelligence depends on or at least benefits from our knowledge of the connection between space and logic.
The matter is that spatial visualizations are an important ability in logical and mathematical thinking as such. The logical square of opposition and the four figures of syllogisms became not only the first symbolic-logical tool, but also the first visualization of logical reasoning. Abstract machines thought up since Alan Turing were to present a visualization of computations, too. In turn, these abstract machines were a continuation of old logical tradition of diagrammatic reasoning. This tradition was established in the medieval magic literature of Arabic, Hebrew, and Latin authors from the 12th to the 13th century, which described some numerical tools as a kind of logical machines that were well formally explicated much later by Gottfried Wilhelm von Leibniz (1646 –1716) as the famous characteristica universalis (universal characteristic). Hence, the diagrammatic reasoning implemented later in Turing machines has a rich history and pre-history.
By now, there are three main approaches to diagrammatic reasoning we would like to present in our special issue: logical, programming, and engineering. In the first (logical) approach, various diagrams for explicating logical notions and relations are studied. In the programming approach, different process calculi for a logical analysis of processes from business and other types of human and robot activity are developed. In the engineering approach, different natural processes are regarded as specific abstract machines. The latter direction of investigation is called unconventional computing. Here any natural process is regarded as a kind of visual computation, such as DNA computing, reaction-diffusion computing, social insects computing, etc. As a result, nature itself is considered a visual demonstration of computations that we can learn.
So, this special issue of Logica Universalis is devoted to diagrammatic reasoning in general and visual demonstrations of computations and logical thinking. The aim is to bring together logicians or philosophers dealing with diagrammatic tools with researchers dealing with explicating processes in human actions and in nature itself by means of considering biological, bio-inspired, chemical, physical, etc. computing to initiate development of novel diagrammatic paradigms.
The topics of interest include, but are not limited to:
Pre-history and history of abstract machines
Abstract machines in nature
Diagrammatic tools for logic
Slime mould computing
Social insects computing
Computational models of cognition
15 July 2021
Notification of full papers:
15 September 2021
Publication of full papers in Logica Universalis (Springer):
#Pre-history and history of abstract machines, #Abstract machines in nature, #Diagrammatic tools for logic, #Diagrammatic reasoning, #Spatial logic, #Spatial algorithms, #Process calculi, #Slime mould computing, #Social insects computing, #Bio-molecular computing, #Unconventional computing, #Computational models of cognition