An Optimal Seed-Identification and Generation Analysis Algorithm for Self-Reproducing Systems
- Paper number
IAC-07-D3.2.02
- Author
Mr. Amor Menezes, University of Michigan, United States
- Coauthor
Dr. Pierre Kabamba, University of Michigan, United States
- Year
2007
- Abstract
This paper is motivated by the need to minimize the payload mass required to establish an extraterrestrial robotic colony. One approach is to create a colony consisting of individual robots endowed with the capacity for self-reproduction. The possibilities of this approach have been analyzed over the past twenty-five years, and NASA and the research community have proposed various concept designs for a self-reproducing lunar robotic colony. These concepts have yet to be realized due to the nascent stage of the technology. An important consideration for the establishment of a self-reproducing robotic colony is the identification of a seed. Prior work having dealt with this problem, this paper will outline a novel algorithm to determine the optimal seed for a class of generation systems, and illustrate the application of the algorithm on several self-replicating systems documented in the literature. Use of this algorithm is thus a stepping-stone towards successful artificial self-reproduction.
The technical methods employed in this paper utilize concepts from Generation Theory, which aid in the analysis of self-reproducing generation systems. Self-reproduction is achieved by the actions of a robot on available resources, and so a seed for the colony consists of a set of robots and a set of resources. In a previous approach to the seeding problem, a Seed-Identification and Generation Analysis algorithm included certain restrictive assumptions about the generation system under consideration, but, in some cases, unfortunately made non-optimal seeds possible. The original content in this paper examines those assumptions and makes suitable modifications to overcome their limitations. The relationship between the size of the seed and the characteristics of a generation system are also specified in this work. Further, the necessary and sufficient conditions to produce an optimal seed are developed for the first time. The demonstration that the proposed algorithm produces an optimal seed is made by indicating how these conditions are satisfied, and by examining a number of hypothetical and real/proposed generation systems for which an optimal seed can be pre-determined. The conclusion that this is an Optimal Seed-Identification and Generation Analysis algorithm is made.
This work is applicable to any system that requires adaptable robots be operated in a resource-constrained environment. It is expected that this paper will assist in moving from analyzing self-reproducing generation systems to synthesizing them.
- Abstract document
- Manuscript document
IAC-07-D3.2.02.pdf (🔒 authorized access only).
To get the manuscript, please contact IAF Secretariat.