In this paper we investigate why solving leximin fuzzy constraint satisfaction problems (FCSP) with non-enumerative algorithms, such as hill-climbing, simulated annealing and genetic algorithms, provide disappointing results. Specifically, we analyse the structure and properties of the leximin FCSPs and its influence on the search strategy of non-enumerative algorithms.

We describe the use of a Genetic Algorithm (GA) for the Unit Selection problem, which is essentially a search/optimization problem. The various operators for the GA have been defined and comparison with optimization reached by hill climbing approaches is presented.

The method of nearest-neighbor interchange effects local improvements in a binary tree by replacing a 4-subtree by one of its two alternatives if this improves the objective function. We extend this to k-subtrees to reduce the number of local optima. Possible sequences of k-subtrees to be examined are produced by moving a window over the tree, incorporating one edge at a time while deactivating...

This paper introduces a new approximate inference algorithm for credal networks. The algorithm consists of two major steps. It starts by representing the credal network as a compiled logical theory. The resulting graphical structure is the basis on which the subsequent steepest-ascent hill-climbing algorithm operates. The output of the algorithm is an inner approximation of the exact lower and ...

We study how the complexity of evolutionary dynamics in the classic MacArthur consumerresource model depends on resource uptake and utilization rates. The traditional assumption in such models is that the utilization rate of the consumer is proportional to the uptake rate. More generally, we show that if these two rates are related through a power law (which includes the traditional assumption ...

An experimental study of a sand bed submitted to a transient water shear flow in a vertical axis cylindrical container is reported. The appearance of spontaneous phase segregation in the spiral ripple patterns is shown. Larger grains are observed to segregate on the downstream part of the ripples, while the smaller ones segregate on the upstream part. The relative repose angles between sand spe...

An experimental study of a binary granular mixture submitted to a transient shear flow in a cylindrical container is reported. The formation of ripples with a spiral shape is observed. The appearance of phase segregation in those spiral patterns is shown. The relative grain size bewteen sand species is found to be a relevant parameter leading to phase segregation. However, the relative repose a...

Genetic algorithms have particular potential as a tool for optimization when the evaluation function is noisy. Several types of genetic algorithm are compared against a mutation driven stochastic hill-climbing algorithm on a standard set of benchmark functions which have had Gaussian noise added to them. Diierent criteria for judging the eeectiveness of the search are also considered. The genet...

Analog Gradient Search This analog phase demodulation hill-climbing technique works for clean, quasi-Gaussian couplings already near optimal alignment. However it will lock-in on local maxima and “flat spots” which occur in multimode couplings, with imperfect devices, or far from optimum alignment. Nevertheless, instrumentation based on this principle was popular, though bulky and providing too...

We consider the problem of learning to act in partially observable, continuous-state-and-action worlds where we have abstract prior knowledge about the structure of the optimal policy in the form of a distribution over policies. Using ideas from planning-as-inference reductions and Bayesian unsupervised learning, we cast Markov Chain Monte Carlo as a stochastic, hill-climbing policy search algo...