Skip Nav Destination
Close Modal
Update search
NARROW
Format
Journal
TocHeadingTitle
Date
Availability
1-6 of 6
Dominique Chu
Close
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Sort by
Journal Articles
Publisher: Journals Gateway
Artificial Life (2008) 14 (3): 313–323.
Published: 01 July 2008
Abstract
View article
PDF
While complex systems have been studied now for more than two decades, there still is no agreement on what complexity actually is. This lack of a definition might be a problem when asking questions about the evolution of complexity. In this article criteria against which candidate measures of complexity can be assessed are discussed. The main conclusion of this article is that because of the absence of a basic consensus on what complexity is, there is no criterion that can be used to decide whether or not a proposed measure actually measures complexity. The main recommendation is to abandon complexity as a formal notion; instead, research into the evolution of complexity should use well-understood proxy notions (as is sometimes done in the literature). For the time being “complexity” should remain an informal notion. Research into evolutionary trends of these proxy notions might eventually lead to an emergent community consensus on what complexity is.
Journal Articles
Publisher: Journals Gateway
Artificial Life (2007) 13 (4): 369–381.
Published: 01 October 2007
Abstract
View article
PDF
Robert Rosen's central theorem states that organisms are fundamentally different from machines, mainly because they are “closed with respect to effcient causation.” The proof for this theorem rests on two crucial assumptions. The first is that for a certain class of systems (“mechanisms”) analytic modeling is the inverse of synthetic modeling. The second is that aspects of machines can be modeled using relational models and that these relational models are themselves refined by at least one analytic model. We show that both assumptions are unjustified. We conclude that these results cast serious doubts on the validity of Rosen's proof.
Journal Articles
Publisher: Journals Gateway
Artificial Life (2007) 13 (3): 299–302.
Published: 01 July 2007
Abstract
View article
PDF
In a recent article in Artificial Life , Chu and Ho suggested that Rosen's central result about the simulability of living systems might be flawed. This argument was later declared “null and void” by Louie. In this article the validity of Louie's objections are examined.
Journal Articles
Publisher: Journals Gateway
Artificial Life (2006) 12 (1): 117–134.
Published: 01 January 2006
Abstract
View article
PDF
One of Robert Rosen's main contributions to the scientific community is summarized in his book Life itself. There Rosen presents a theoretical framework to define living systems; given this definition, he goes on to show that living systems are not realizable in computational universes. Despite being well known and often cited, Rosen's central proof has so far not been evaluated by the scientific community. In this article we review the essence of Rosen's ideas leading up to his rejection of the possibility of real artificial life in silico. We also evaluate his arguments and point out that some of Rosen's central notions are ill defined. The conclusion of this article is that Rosen's central proof is wrong.
Journal Articles
Publisher: Journals Gateway
Artificial Life (2005) 11 (4): 403–405.
Published: 01 October 2005
Journal Articles
Publisher: Journals Gateway
Artificial Life (2005) 11 (3): 317–338.
Published: 01 July 2005
Abstract
View article
PDF
The DNA of some naturally competent species of bacteria contains a large number of evenly distributed copies of a short sequence. This highly overrepresented sequence is believed to be an uptake signal sequence (USS) that helps bacteria to take up DNA selectively from (dead) members of their own species. For some time it has been assumed that the USS evolved in order to enable bacteria to distinguish between conspecific and nonconspecific DNA fragments (the preference-first hypothesis). Recently, Redfield suggested that this hypothesis is not in fact realistic, as it would require biologically implausible group selection. In this article we present a model designed to demonstrate the emergence of similar USSs in a population of simulated evolving agents. We use this model to examine the conditions under which a USS will emerge in a preference-first scenario.