2,278 research outputs found
Parallel Ada benchmarks for the SVMS
The use of parallel processing paradigm to design and develop faster and more reliable computers appear to clearly mark the future of information processing. NASA started the development of such an architecture: the Spaceborne VHSIC Multi-processor System (SVMS). Ada will be one of the languages used to program the SVMS. One of the unique characteristics of Ada is that it supports parallel processing at the language level through the tasking constructs. It is important for the SVMS project team to assess how efficiently the SVMS architecture will be implemented, as well as how efficiently Ada environment will be ported to the SVMS. AUTOCLASS II, a Bayesian classifier written in Common Lisp, was selected as one of the benchmarks for SVMS configurations. The purpose of the R and D effort was to provide the SVMS project team with the version of AUTOCLASS II, written in Ada, that would make use of Ada tasking constructs as much as possible so as to constitute a suitable benchmark. Additionally, a set of programs was developed that would measure Ada tasking efficiency on parallel architectures as well as determine the critical parameters influencing tasking efficiency. All this was designed to provide the SVMS project team with a set of suitable tools in the development of the SVMS architecture
Where are Bottlenecks in NK Fitness Landscapes?
Usually the offspring-parent fitness correlation is used to visualize and
analyze some caracteristics of fitness landscapes such as evolvability. In this
paper, we introduce a more general representation of this correlation, the
Fitness Cloud (FC). We use the bottleneck metaphor to emphasise fitness levels
in landscape that cause local search process to slow down. For a local search
heuristic such as hill-climbing or simulated annealing, FC allows to visualize
bottleneck and neutrality of landscapes. To confirm the relevance of the FC
representation we show where the bottlenecks are in the well-know NK fitness
landscape and also how to use neutrality information from the FC to combine
some neutral operator with local search heuristic
Measuring the Evolvability Landscape to study Neutrality
This theoretical work defines the measure of autocorrelation of evolvability
in the context of neutral fitness landscape. This measure has been studied on
the classical MAX-SAT problem. This work highlight a new characteristic of
neutral fitness landscapes which allows to design new adapted metaheuristic
Ada in AI or AI in Ada. On developing a rationale for integration
The use of Ada as an Artificial Intelligence (AI) language is gaining interest in the NASA Community, i.e., by parties who have a need to deploy Knowledge Based-Systems (KBS) compatible with the use of Ada as the software standard for the Space Station. A fair number of KBS and pseudo-KBS implementations in Ada exist today. Currently, no widely used guidelines exist to compare and evaluate these with one another. The lack of guidelines illustrates a fundamental problem inherent in trying to compare and evaluate implementations of any sort in languages that are procedural or imperative in style, such as Ada, with those in languages that are functional in style, such as Lisp. Discussed are the strengths and weakness of using Ada as an AI language and a preliminary analysis provided of factors needed for the development of criteria for the integration of these two families of languages and the environments in which they are implemented. The intent for developing such criteria is to have a logical rationale that may be used to guide the development of Ada tools and methodology to support KBS requirements, and to identify those AI technology components that may most readily and effectively be deployed in Ada
Scuba Search : when selection meets innovation
We proposed a new search heuristic using the scuba diving metaphor. This
approach is based on the concept of evolvability and tends to exploit
neutrality in fitness landscape. Despite the fact that natural evolution does
not directly select for evolvability, the basic idea behind the scuba search
heuristic is to explicitly push the evolvability to increase. The search
process switches between two phases: Conquest-of-the-Waters and
Invasion-of-the-Land. A comparative study of the new algorithm and standard
local search heuristics on the NKq-landscapes has shown advantage and limit of
the scuba search. To enlighten qualitative differences between neutral search
processes, the space is changed into a connected graph to visualize the
pathways that the search is likely to follow
Anisotropic selection in cellular genetic algorithms
In this paper we introduce a new selection scheme in cellular genetic
algorithms (cGAs). Anisotropic Selection (AS) promotes diversity and allows
accurate control of the selective pressure. First we compare this new scheme
with the classical rectangular grid shapes solution according to the selective
pressure: we can obtain the same takeover time with the two techniques although
the spreading of the best individual is different. We then give experimental
results that show to what extent AS promotes the emergence of niches that
support low coupling and high cohesion. Finally, using a cGA with anisotropic
selection on a Quadratic Assignment Problem we show the existence of an
anisotropic optimal value for which the best average performance is observed.
Further work will focus on the selective pressure self-adjustment ability
provided by this new selection scheme
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