Entropy

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Open AccessArticle

Complex Intelligent Systems: Juxtaposition of Foundational Notions and a Research Agenda

by Petros A.M. Gelepithis

Entropy 2001, 3(4), 247-258; https://0-doi-org.brum.beds.ac.uk/10.3390/e3040247 - 01 Dec 2001

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The cardinality of the class, C , of complex intelligent systems, i.e., systems of intelligent systems and their resources, is steadily increasing. Such an increase, whether designed, sometimes changes significantly and fundamentally, the structure of C . Recently,the study of members of C [...] Read more.

The cardinality of the class, C , of complex intelligent systems, i.e., systems of intelligent systems and their resources, is steadily increasing. Such an increase, whether designed, sometimes changes significantly and fundamentally, the structure of C . Recently,the study of members of C and its structure comes under a variety of multidisciplinary headings the most prominent of which include General Systems Theory, Complexity Science, Artificial Life, and Cybernetics. Their common characteristic is the quest for a unified theory of a certain class of systems like a living system or an organisation. So far, the only candidate for a general theory of intelligent systems is Newell's Soar. To my knowledge there is presently no candidate theory of C except Newell's claimed extensibility of Soar. This paper juxtaposes the elements of Newell's conceptual basis with those of an alternative conceptual framework based on the thesis that communication and understanding are the primary processes shaping the structure of C and its members. It is patently obvious that a research agenda for the study of C can be extremely varied and long. The third section of this paper presents a highly selective research agenda that aims to provoke discussion among complexity theory scientists. Full article

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114 KiB

Open AccessArticle

A Possible Extension of Shannon's Information Theory

by Takuya Yamano

Entropy 2001, 3(4), 280-292; https://0-doi-org.brum.beds.ac.uk/10.3390/e3040280 - 21 Nov 2001

Cited by 22 | Viewed by 7616

Abstract

As a possible generalization of Shannon's information theory, we review the formalism based on the non-logarithmic information content parametrized by a real number q, which exhibits nonadditivity of the associated uncertainty. Moreover it is shown that the establishment of the concept of [...] Read more.

As a possible generalization of Shannon's information theory, we review the formalism based on the non-logarithmic information content parametrized by a real number q, which exhibits nonadditivity of the associated uncertainty. Moreover it is shown that the establishment of the concept of the mutual information is of importance upon the generalization. Full article

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335 KiB

Open AccessArticle

Self-Organization of Template-Replicating Polymers and the Spontaneous Rise of Genetic Information

by Jarle Breivik

Entropy 2001, 3(4), 273-279; https://0-doi-org.brum.beds.ac.uk/10.3390/e3040273 - 20 Nov 2001

Cited by 33 | Viewed by 10802

Abstract

Living systems imply self-reproducing constructs capable of Darwinian evolution. How such dynamics can arise from undirected interactions between simple monomeric objects remains an open question. Here we circumvent difficulties related to the manipulation of chemical interactions, and present a system of ferromagnetic objects [...] Read more.

Living systems imply self-reproducing constructs capable of Darwinian evolution. How such dynamics can arise from undirected interactions between simple monomeric objects remains an open question. Here we circumvent difficulties related to the manipulation of chemical interactions, and present a system of ferromagnetic objects that self-organize into template-replicating polymers due to environmental fluctuations in temperature. Initially random sequences of monomers direct the formation of complementary sequences, and structural information is inherited from one structure to another. Selective replication of sequences occurs in dynamic interaction with the environment, and the system demonstrates the fundamental link between thermodynamics, information theory, and life science in an unprecedented manner. Full article

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111 KiB

Open AccessArticle

Empirical Evidence for a Law of Information Growth

by Richard L. Coren

Entropy 2001, 3(4), 259-272; https://0-doi-org.brum.beds.ac.uk/10.3390/e3040259 - 20 Nov 2001

Cited by 9 | Viewed by 6047

Abstract

Based on a robust, phenomenological model for the growth of a system parameter, a relation is derived to test the evolution of such a parameter through several distinct stages. It is found that data defining the acknowledged major changes in the evolution of [...] Read more.

Based on a robust, phenomenological model for the growth of a system parameter, a relation is derived to test the evolution of such a parameter through several distinct stages. It is found that data defining the acknowledged major changes in the evolution of earth, the life on it, and cultural and technological growth, conform to this model. The nature of these altering events indicates that information is the parameter involved, suggesting an unrecognized behavior in the Second Law of Thermodynamics. Full article

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153 KiB

Open AccessArticle

Major Transitions in Language Evolution

by Joshua B. Plotkin and Martin A. Nowak

Entropy 2001, 3(4), 227-246; https://0-doi-org.brum.beds.ac.uk/10.3390/e3040227 - 10 Oct 2001

Cited by 6 | Viewed by 7920

Abstract

Language is the most important evolutionary invention of the last few million years. How human language evolved from animal communication is a challenging question for evolutionary biology. In this paper we use mathematical models to analyze the major transitions in language evolution. We [...] Read more.

Language is the most important evolutionary invention of the last few million years. How human language evolved from animal communication is a challenging question for evolutionary biology. In this paper we use mathematical models to analyze the major transitions in language evolution. We begin by discussing the evolution of coordinated associations between signals and objects in a population. We then analyze word-formation and its relationship to Shannon's noisy coding theorem. Finally, we model the population dynamics of words and the adaptive emergence of syntax. Full article

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Entropy, Volume 3, Issue 4 (November 2001) – 5 articles , Pages 227-292

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