José M. Sempere

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In this paper we consider networks of evolutionary processors as language generating and computational devices. When the filters are regular languages one gets the computational power of Turing machines with networks of size at most six, depending on the underlying graph. When the filters are defined by random context conditions, we obtain an(More)
In this paper, we study the notion of k-reversibility and k-testability when regular tree languages are involved. We present an inference algorithm for learning a k-testable tree language that runs in polynomial time with respect to the size of the sample used. We also study the tree language classes in relation to other well known ones, and some properties(More)
In this note we solve a problem left open in [2]: namely, we show that the iterated superposition of a regular language is regular. The proof of this result is based on two facts: (i) the iterated superposition of a language equals the restricted iterated superposition of the same language, (ii) the sequence formed by iteratively applying the restricted(More)
In this paper we simplify the model of computation considered in [1], namely network of evolutionary picture processors, by moving the filters from the nodes to the edges. Each edge is now viewed as a twoway channel such that input and output filters, respectively, of the two nodes connected by the edge coincide. Thus, the possibility of controlling the(More)
We propose a computational device based on evolutionary rules and communication within a network, similar to that introduced in [4], called network of evolutionary processors. An NP-complete problem is solved by networks of evolutionary processors of linear size in linear time. Some furher directions of research are finally discussed. ∗Research supported by(More)
The rapid growth of protein sequence databases is exceeding the capacity of biochemically and structurally characterizing new proteins. Therefore, it is very important the development of tools to locate, within protein sequences, those subsequences with an associated function or specific feature. In our work, we propose a method to predict one of those(More)