Evolutionary dynamics of cellular automata-based self-replicators in hostile environments

Salzberg, Chris; Antony, Antony; Sayama, Hiroki

doi:10.1016/j.biosystems.2004.07.004

Cited by 16 publications

(9 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To illustrate the effectiveness of the proposed visualization method, we compare the above result with evolutionary dynamics in the presence of the pathogenic environment introduced in [13]. This environment consists of a newly added tenth state that we call pathogen, as well as an added CA layer.…”

Section: Resultsmentioning

confidence: 95%

“…The effect of this new environment is twofold: to open free space and to dynamically partition the periodic domain, as seen in Figure 4. The combination of these effects has been found to encourage sustainable diversity, leading to evolutionary accessibility to larger species and a limited form of complexity increase [13]. Figures 5 and 6 depict population dynamics and genealog y exploration starting with the same ancestral species (GGCCGGCGCGTTGCGC/8 Â 8), now coupled with the pathogenic environment.…”

Section: Resultsmentioning

confidence: 97%

“…We then use an iterative relaxation scheme to map the nodes and links of its genealog y graphs to a 2D visualization space, purely on the basis of genealog y-space topolog y. The introduction of a pathogenic environment [13] is used to demonstrate the insight gained by this approach.…”

Section: Example: Evoloop With Pathogenic Environmentmentioning

confidence: 99%

“…We highlight the effectiveness of our approach by comparing the evolutionary dynamics of loops under two different environmental settings: one with the original state transition rules and one with a newly introduced pathogen state [13]. The proposed approach using graph-based genealog y successfully captures the critical role played by dynamic habitat partitioning in the maintenance of evolutionary exploration behavior.…”

Section: Introductionmentioning

confidence: 97%

See 3 more Smart Citations

Visualizing Evolutionary Dynamics of Self-Replicators: A Graph-Based Approach

2006

Self Cite

View full text Add to dashboard Cite

We present a general approach for evaluating and visualizing evolutionary dynamics of self-replicators using a graph-based representation for genealogy. Through a transformation from the space of species and mutations to the space of nodes and links, evolutionary dynamics are understood as a flow in graph space. A formalism is introduced to quantify such genealogical flows in terms of the complete history of localized evolutionary events recorded at the finest level of detail. Represented in a multidimensional viewing space, collective dynamical properties of an evolving genealogy are characterized in the form of aggregate flows. We demonstrate the effectiveness of this approach by using it to compare the evolutionary exploration behavior of self-replicating loops under two different environmental settings.

show abstract

Section: Resultsmentioning

confidence: 95%

Section: Resultsmentioning

confidence: 97%

Section: Example: Evoloop With Pathogenic Environmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

See 2 more Smart Citations

Visualizing Evolutionary Dynamics of Self-Replicators: A Graph-Based Approach

2006

Self Cite

View full text Add to dashboard Cite

show abstract

“…Such species thus have mutational tendencies extremely biased toward larger sizes [the top-5 sequences in Figure 2(b) turned out to be of this kind]. It is also experimentally confirmed that evolutionary descendants of these species generally inherit their mutational biases [19].…”

mentioning

confidence: 82%

Complex genetic evolution of artificial self‐replicators in cellular automata

Salzberg

Sayama

2004

Complexity

Self Cite

View full text Add to dashboard Cite

It is widely believed that evolutionary dynamics of artificial self-replicators realized in cellular automata (CA) Key Words: cellular automata; self-replication; genetic evolution; diversity; adaptation S ince von Neumann's work on self-reproducing automata [1], artificial self-replication models based on cellular automata (CA) have formed one of the mainstreams in artificial life [2][3][4][5]. Recent developments indicate that simple CA with fixed rules can reproduce natural selection among different self-replicating structures [6,7], yet their evolutionary dynamics are considered quite limited in both diversity and adaptive behavior [8,9]. Contrary to these earlier observations, we show that genetic adaptation and diversification processes may occur in such simple CA. We investigate a system of evolving self-replicating loops, or evoloops [7], in which replication, variation and selection emerge solely from fixed local rules. Applying new tools for detailed genetic identification and genealogy tracing [10], we uncovered a genotypic permutation space that expands combinatorially with replicator size, within which loops exhibit significant diversity in macro-scale morphologies and mutational biases. Populations undergo nontrivial genetic adaptation, maximizing colony density while enhancing sustainability against other species. We also identified a set of nonmutable subsequences in the evoloop genetics, with which one can carry out genetic operations to alter fitness differentials and promote long-term evolutionary exploration. This effect is further manifested when populations are introduced to a hostile environment. These results demonstrate a unique example of genetic evolution that traverses multiple scales, hierarchically emerging from local interactions between elements much smaller than individual replicators.

show abstract