The legacy of Wilson’s XCS is that modern Learning Classifier Systems can be characterized by their use of rule accuracy as the utility metric for the search algorithm(s) discovering useful rules. Such searching typically takes place within the restricted space of co-active rules for efficiency. This paper gives an historical overview of the evolution of such systems up to XCS, and then some of...

Many modern video surveillance systems encompass pan-tilt cameras due to the flexibility they provide in selecting the fields-of-view, as compared to using just fixed cameras. Although patent the great potential of using the pan-tilt cameras, one has to design pan and tilt controllers whose effectiveness directly impacts on the surveillance performance. In this work we propose a metric tuned to...

For a case-based application with a sizable case library, a common practice is to retrieve a set of cases and then reduce the set with a domain-specific similarity metric. This research investigates an alternative technique that constructs a number of two-dimensional (or multi-dimensional) indices using the principle of elaboration and specialization. By storing cases with these indices, we red...

The statistical physics approach to the number partioning problem, a classical NPhard problem, is both simple and rewarding. Very basic notions and methods from statistical mechanics are enough to obtain analytical results for the phase boundary that separates the “easy-to-solve” from the “hard-to-solve” phase of the NPP as well as for the probability distributions of the optimal and sub-optima...

In two samples, we demonstrate that visual search performance is influenced by memory for the locations of specific search items across trials. We monitored eye movements as observers searched for a target letter in displays containing 16 or 24 letters. From trial to trial the configuration of the search items was either Random, fully Repeated or similar but not identical (i.e., Intermediate). ...

Our work on the subject of search has been motivated by a variety of applications in engineering and technology, and it differs from the physicists’ motivation for such problems, e.g., or the motivation provided by biochemistry, and in theoretical biology . One of our reasons for a more fundamental approach to search comes from the area of traffic routing in wired networks where each end user m...

Many machine learning algorithms have hyperparameters flags, values, and other configuration information that guides the algorithm. Sometimes this configuration applies to the space of functions that the learning algorithm searches (e.g. the number of nearest neighbours to use in KNN). Sometimes this configuration applies to the way in which the search is conducted (e.g. the step size in stocha...

Introduction. The problems of search dealt with in this paper can be described by the following simple model. Let Sn be a finite set having n^2 distinguishable elements—called points—and suppose that we want to find an unknown point x of the set Sn; the set Sn itself is supposed to be known to us. Let us suppose further that it is not possible to observe x directly, however we may choose some f...

Ž . ABSTRACT: In a randomly grown binary search tree BST of size n, any fixed pattern occurs with a frequency that is on average proportional to n. Deviations from the average case are highly unlikely and well quantified by a Gaussian law. Trees with forbidden patterns occur with an exponentially small probability that is characterized in terms of Bessel functions. The results obtained extend t...

We give a practical random mapping that takes any set of documents represented as vectors inEuclidean space and then maps them to a sparse subset of the Hamming cube while retaining ordering ofinter-vector inner products. Once represented in the sparse space, it is natural to index documents usingcommercial text-based search engines which are specialized to take advantage of thi...