This paper introduces the gene expression messy genetic algorithm (GEMGA)|a new generation of messy GAs that may nd many applications in nan-cial engineering. Unlike other existing blackbox optimization algorithms, GEMGA directly searches for relations among the members of the search space. The GEMGA is an O(jj k (` + k)) sample complexity algorithm for the class of order-k delineable problems ...

Characterizing and understanding social-ecological systems (SESs) is increasingly necessary to answer questions about the development of sustainable human settlements. To date, much of the literature on SES analysis has focused on “neat” systems involving a single type of resource, a group of users, and a governance system. While these studies provide valuable and specific insights, they are of...

Disadvantages of traditional reinforcement learning techniques are complicated structures and that training algorithms are often reliant on the derivative information of the problem domain and also require a priori information of the network architecture. Such handicaps are overcome in this paper with the use of ‘messy genetic algorithms’, whose main characteristic is a variable length chromoso...

Many real-world scientific and engineering applications involve finding solutions to “hard” Multiobjective Optimization Problems (MOPs). Genetic Algorithms (GAs) can be extended to find acceptable MOP Pareto solutions. The intent of this discussion is to illustrate that modifications made to the Multi-Objective messy GA (MOMGA) have further improved the efficiency of the algorithm. The MOMGA is...

Fuzzy logic controllers have been applied to a wide range of control problems, but are very difficult to build for situations where the environment changes quickly and there is a lot of uncertainty. This work investigates a new method of creating fuzzy controllers, in the form of reactive agents, for such environments. The framework for this investigation is the RoboCup soccer simulation enviro...

This paper makes an eeort to project the theoretical lessons of the SEARCH (Search Envisioned As Relation and Class Hierarchizing) framework introduced elsewhere (Kargupta, 1995; Kargupta & Goldberg, 1996) in the context of natural evolution (Kargupta, 1996c) and introduce the gene expression messy genetic algorithm (Kargupta, 1996a; Kargupta, 1996b) (GEMGA)|a new generation of messy GAs that d...

Successful recombination in the simple GA requires that interdependent genes be close to each other on the genome. Several methods have been proposed to reorder genes on the genome when the given ordering is unfavorable. The Messy GA (MGA) is one such ‘moving-locus’ scheme. However, gene reordering is only part of the Messy picture. The MGA uses another mechanism that is influential in enabling...

Fuzzy logic controllers have been applied to a wide range of control problems, but are very difficult to build for situations where the environment changes quickly and there is a lot of uncertainty. This work investigates a new method of creating fuzzy controllers, in the form of reactive agents, for such environments. The framework for this investigation is the RoboCup soccer simulation enviro...

Theoretical perspectives of science communication were initially driven by practice, which in turn have influenced practice and further scholarship. The includes a variety quite diverse roles. Likewise, the scholarship draws upon mix disciplines. I argue that apparent messiness is also its wealth. If blame can be avoided developing applying models, if coexistence all models embraced then both l...