Studying Arti cial Life Using a Simple

نویسنده

  • Moshe Sipper
چکیده

Some of the major outstanding problems in biology are related to issues of emergence and evolution. These include: (1) how do populations of organisms traverse their adaptive landscapes? (2) what is the relation between adaptedness and tness? (3) the formation of multi-cellular organisms from basic units or cells. In this paper we study these issues using a model which is both general and simple. The system, derived from the CA (cellular au-tomata) model, consists of a two-dimensional grid of interacting organisms which may evolve over time. We rst present designed multi-cellular organisms which display several interesting behaviors including: reproduction, growth, mobility. We then turn our attention to evolution in various environments , including: an environment in which competition for space occurs, an IPD (Iterated Prisoner's Dilemma) environment, an environment of spatial niches, and an environment of temporal niches. One of the advantages of AL models is the opportunities they ooer in performing in-depth studies of the evolutionary process. This is accomplished in our case by observing not only phenotypic eeects but also such measures as: tness, operability, energy and the genescape. Our work sheds light on the problems raised above, and ooers a possible path towards the long term twofold goal of ALife research: (1) increasing our understanding of biology and (2) enhancing our understanding of artiicial models, thereby providing us with the ability to improve their performance.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Genetic Algorithms and Artiicial Life

Genetic algorithms are computational models of evolution that play a central role in many arti cial-life models. We review the history and current scope of research on genetic algorithms in arti cial life, using illustrative examples in which the genetic algorithm is used to study how learning and evolution interact, and to model ecosystems, immune system, cognitive systems, and social systems....

متن کامل

Genetic Algorithms and Artificial Life

Genetic algorithms are computational models of evolution that play a central role in many arti cial life models We review the history and current scope of research on genetic algorithms in arti cial life using illustrative examples in which the genetic algorithm is used to study how learning and evolution interact and to model ecosystems immune system cognitive systems and social systems We als...

متن کامل

ALife Meets Web: Lessons Learned

Arti cial life might come to play important roles for the World Wide Web, both as a source of new algorithmic paradigms and as a source of inspiration for its future development. New Web searching and managing techniques, based on arti cial life principles, have been elicited by the striking similarities between the Web and natural environments. New Web interface designs, based on arti cial lif...

متن کامل

Dimensions of Neural-symbolic Integration - A Structured Survey

Research on integrated neural-symbolic systems has made signi cant progress in the recent past. In particular the understanding of ways to deal with symbolic knowledge within connectionist systems (also called arti cial neural networks) has reached a critical mass which enables the community to strive for applicable implementations and use cases. Recent work has covered a great variety of logic...

متن کامل

Limitations of Scienti c Ontology

Arti cial life is a new multi disciplinary science which is emerging from established practices in arti cial intelligence computational biology and cybernetics It is argued in this paper that conventional scienti c con cepts of being and existence i e ontology which underpin most of our attempts to create arti cial life and intelligent systems are inadequate to deal with these issues It is argu...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1995