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We need much better understanding of information processing and
comp
u-
tation
as
its pri
mary form
.
Future
progress
of new computational devices capable of
dealing with problems of big data, internet of things, semantic web, co
g
nitive robotics
and neuroinformatics
depends on the
adequate
models of computation.
In this article
w
e
first
present...
Context in source publication
Context 1
... Computational Triad reflects the structure of the world represented by the Existential Triad (Burgin, 2012). The Existential Triad develops the tradition of Plato, Aristotle and Popper, and is presented in Figure 3, giving a consistent understanding and scientifically grounded interpretation of Plato ideas. Here the physical (material) world is interpreted as the physical reality studied by natural sciences, the mental world encompasses different levels of mentality (cognition), and the world of structures consists of various forms and types of structures. ...
Citations
... At the same time there is parallel computation, and multilevel computation, non-local computation as well as distributed computation, fuzzy and random computation very much as also quantum computation and emergent computation, not to mention interactive computation. A typology of computation and computational models can be seen in [12]. A metaphor can be introduced here, namely a variety of computations corresponds to the diversity of life and living beings. ...
... It should also be noted that methodological reflection on the nature of computation has already resulted in first classifications. Of particular interest is the proposal by Mark Burgin and Gordana Dodig-Crnkovic presented in their overview work on the concept of computations (Burgin and Dodig-Crnkovic, 2013). It is worth quoting the said attempt at classification to show the diversity of contexts in which the problems of computational processes are considered. ...
This article presents the evolution of philosophical and methodological considerations concerning empiricism in computer/computing science. In this study, we trace the most important current events in the history of reflection on computing. The forerunners of Artificial Intelligence H.A. Simon and A. Newell in their paper Computer Science As Empirical Inquiry (1975) started these considerations. Later the concept of empirical computer science was developed by S.S. Shapiro, P. Wegner, A.H. Eden and P.J. Denning. They showed various empirical aspects of computing. This led to a view of the science of computing (or science of information processing) - the science of general scope. Some interesting contemporary ways towards a generalized perspective on computations were also shown (e.g. natural computing).
... Intrinsic natural computation occurs on variety of levels of physical processes, such as the levels of computation of living organisms as well as designed computational devices. The present article is building on our typology of models of computation as information processing (Burgin & Dodig-Crnkovic, 2013). It is indicating future paths for the advancement of the field, expected both as a result of the development of new computational models and learning from nature how to better compute using information transformation mechanisms of intrinsic computation. ...
... Variety of current approaches to the concept of computation shows remarkable complexity that makes communication of related results and ideas increasingly difficult. We explicated present diversity of concepts and models in (Burgin & Dodig-Crnkovic, 2013) to highlight the necessity of establishing relationships and common understanding. The analysis of the present state of the art allowed us to discover basic structures inherent for computation and to develop a multifaceted typology of computations. ...
Future progress of new information processing devices capable of dealing with problems such as big data, Internet of things, semantic web, cognitive robotics, neuroinformatics and similar, depends on the adequate and efficient models of computation. We argue that defining computation as information transformation, and given that there is no information without representation, the dynamics of information on the fundamental level is physical/ intrinsic/ natural computation (Dodig-Crnkovic, 2011) (Dodig-Crnkovic, 2014). Intrinsic natural computation occurs on variety of levels of physical processes, such as the levels of computation of living organisms as well as designed computational devices. The present article is building on our typology of models of computation as information processing (Burgin & Dodig-Crnkovic, 2013). It is indicating future paths for the advancement of the field, expected both as a result of the development of new computational models and learning from nature how to better compute using information transformation mechanisms of intrinsic computation.
This paper presents taxonomy of models of computation. It includes Existential (Physical, Abstract and Cognitive), Organizational, Temporal, Representational, Domain/Data, Operational, Process-oriented and Level-based taxonomy. It is connected to more general notion of natural computation, intrinsic to physical systems, and particularly to cognitive computation in living organisms and artificial cognitive systems. Computation is often understood through the Turing machine model, in the fields of computability, computational complexity and even as a basis for the present-day computer hardware and software architectures. However, several aspects of computation, even those existing in today's applications, are left outside in this model, thus adequate models of real-time, distributed, self-organized, resource-aware, adaptive, learning computation systems are currently being developed.
This paper connects information with computation and cognition via concept of agents that appear at variety of levels of organization of physical/chemical/cognitive systems – from elementary particles to atoms, molecules, life-like chemical systems, to cognitive systems starting with living cells, up to organisms and ecologies. In order to obtain this generalized framework, concepts of information, computation and cognition are generalized. In this framework, nature can be seen as informational structure with computational dynamics, where an (info-computational) agent is needed for the potential information of the world to actualize. Starting from the definition of information as the difference in one physical system that makes a difference in another physical system – which combines Bateson and Hewitt’s definitions, the argument is advanced for natural computation as a computational model of the dynamics of the physical world, where information processing is constantly going on, on a variety of levels of organization. This setting helps us to elucidate the relationships between computation, information, agency and cognition, within the common conceptual framework, with special relevance for biology and robotics.
