WHEN RELAXATION MEETS ADAPTATION IN COMPLEX ADAPTIVE SYSTEMS: A COMPUTATIONAL STUDY OF TUMORIGENESIS

In complex adaptive systems (CASs), the relaxation based on intra-individual interactions and the adaptation based on sub-individual variations are two fundamental processes entangled to induce great complexity. We analyze the system evolution under multicellular homeostatic regulations coupled with various mutation strategies in computational tumorigenesis as a typical instance to clarify the coupling effect of relaxation and adaptation in CASs. Through visualizing the system dynamics on a synthesized fitness landscape which results from the superposition of the phase diagram and the individual fitness landscape, we entertain a simple theoretical framework that not only helps analyze our simulated multicellular dynamics but is potentially applicable to a broader class of problems in CASs where relaxation and adaptation intertwine. It is stressed that the nonadaptive relaxation process has the essential role in shaping the selective pressure of adaptation as well as in defining the final state of the evolution, whereas it is the rigidity of mutation strategy that determines the complexity of the dynamical process.

Download Full-text

Adaptive Walks and Fitness Peak Climbing: Language Learning as Inducing Adaptive Change in L2 Systems

Nagoya JALT Journal ◽

10.37546/jaltchap.nagoya1.1-2 ◽

2020 ◽

Vol 1 (1) ◽

pp. 29-42

Author(s):

William Kumai

Keyword(s):

Language Learning ◽

Complex Adaptive Systems ◽

Adaptive Systems ◽

Fitness Landscape ◽

Landscape Changes ◽

Competence Level ◽

Fitness Value ◽

Learning Conditions ◽

Complex Adaptive ◽

Adaptive Walks

This paper adopts the perspective of students, groups, and entire classes as being complex adaptive systems, or CAS. Two important concepts from complexity theory, adaptive walks and fitness landscapes, can be used to create optimal language learning conditions for producing changes in students’ L2 systems. Every configuration of L2 traits a student might have can be assigned a fitness value, that is, an L2 competence level. The set of all such values creates an abstract landscape, the fitness landscape. By changing traits, the position on the landscape changes, meaning a student can take a journey on the landscape, known as an adaptive walk, in the search for higher peaks, that is, higher competence. The goal becomes establishing conditions in which adaptive walks are encouraged. Several L2 activities are introduced as applications of these ideas. 学生、グループ、およびクラス全体は、複雑系適応システムと考えられる。複雑系理論における2つの概念、アダプティブ・ウォーク(適応型歩行)とフィットネス・ランドスケープは、言語学習に最適な条件を創り出す一助となる。それぞれの学生は皆、文法や発音など異なるレベルのL2 スキルを保有している。これらのスキルを組み合わせることで全体的な L2 能力すなわちフィットネス・バリューを生み出すことが可能となる。このような異なるレベルの組み合わせによる全てのユニットとそれに伴うフィットネス・バリューはフィットネス・ランドスケーブ(適応度地形)を創りだす。ある L2 スキルが向上または低下する時、フィットネス・バリューは変化する。それによってランドスケープ上の位置が変化する。スキルのレベル変化を通じて学生はアダプティブ・ウォークとして知られるランドスケープを旅する。旅の到達目標は、アダプティブ・ウォークを奨励してランドスケープ上の高位のフィットネルピークを見出すことである。これらの理念の応用としていくつかの L2 アクティビティを導入する。

Download Full-text

Agent-Based Computational Economics: Growing Economies From the Bottom Up

Artificial Life ◽

10.1162/106454602753694765 ◽

2002 ◽

Vol 8 (1) ◽

pp. 55-82 ◽

Cited By ~ 345

Author(s):

Leigh Tesfatsion

Keyword(s):

Complex Adaptive Systems ◽

Adaptive Systems ◽

Computational Study ◽

Computational Economics ◽

Agent Based ◽

Research Areas ◽

Open Questions ◽

Complex Adaptive ◽

Potential Benefits ◽

Number Of Publications

Agent-based computational economics (ACE) is the computational study of economies modeled as evolving systems of autonomous interacting agents. Thus, ACE is a specialization of economics of the basic complex adaptive systems paradigm. This study outlines the main objectives and defining characteristics of the ACE methodology and discusses similarities and distinctions between ACE and artificial life research. Eight ACE research areas are identified, and a number of publications in each area are highlighted for concrete illustration. Open questions and directions for future ACE research are also considered. The study concludes with a discussion of the potential benefits associated with ACE modeling, as well as some potential difficulties.

Download Full-text