Visualizing Evolutionary Dynamics of Self-Replicators Using Graph-Based Genealogy

Salzberg, Chris; Antony, Antony; Sayama, Hiroki

doi:10.1007/978-3-540-39432-7_41

Cited by 6 publications

(3 citation statements)

References 9 publications

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“…We have reported elsewhere [1,10] the emergence of huge genetic and behavioral diversity in the evoloop world using a more sophisticated identification scheme, which is not discussed here in detail.…”

Section: Resultsmentioning

confidence: 99%

Self-Protection and Diversity in Self-Replicating Cellular Automata

Sayama

2004

Artificial Life

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The concept of self-protection, a capability of an organism to protect itself from exogenous attacks, is introduced into the design of artificial evolutionary systems as a possible method to create and maintain diversity in the population. Three different mechanisms of self-protection are considered and implemented on a cellular-automaton-based evolutionary system, the evoloop. Simulation results imply a positive effect of those mechanisms on diversity maintenance, especially when the self-protection is moderate so that it conserves both the attacker and the attacked. This letter briefly reports the models and the simulation results obtained using those models.

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Section: Resultsmentioning

confidence: 99%

Self-Protection and Diversity in Self-Replicating Cellular Automata

Sayama

2004

Artificial Life

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“…To emphasize the generality of our approach, we apply in this article a dynamic mapping that ignores the specifics of identifier structure described above, instead focusing exclusively on the topolog y of genealog y space; this differs from the heuristic mapping scheme presented in earlier literature [11]. We use an iterative relaxation method that treats a collection of nodes and links as a dynamical system whose minimum potential states correspond to visually meaningful configurations in a 2D space.…”

Section: Mapping To a 2d Spacementioning

confidence: 98%

“…In principle, the scheme used to translate graph nodes (species) and links to a visualization space may be arbitrarily defined, depending either on details of identifier structure specific to the model under consideration (as in, e.g., [11]) or purely on graph space topolog y (as in, e.g., Section 3.2). The example we describe in the next section uses an iterative relaxation scheme to map the genealog y of a system of self-replicating loops to a two-dimensional space.…”

Section: Evolution As Flowmentioning

confidence: 99%

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

2006

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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.

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Heredity, Complexity, and Surprise: Embedded Self-Replication and Evolution in CA

Salzberg

Sayama

2004

Lecture Notes in Computer Science

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Visualizing Evolutionary Dynamics of Self-Replicators Using Graph-Based Genealogy

Cited by 6 publications

References 9 publications

Self-Protection and Diversity in Self-Replicating Cellular Automata

Self-Protection and Diversity in Self-Replicating Cellular Automata

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

Heredity, Complexity, and Surprise: Embedded Self-Replication and Evolution in CA

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