Search results for " Automata"
showing 10 items of 436 documents
FO^2 with one transitive relation is decidable
2013
We show that the satisfiability problem for the two-variable first-order logic, FO^2, over transitive structures when only one relation is required to be transitive, is decidable. The result is optimal, as FO^2 over structures with two transitive relations, or with one transitive and one equivalence relation, are known to be undecidable, so in fact, our result completes the classification of FO^2-logics over transitive structures with respect to decidability. We show that the satisfiability problem is in 2-NExpTime. Decidability of the finite satisfiability problem remains open.
A Hierarchical Learning Scheme for Solving the Stochastic Point Location Problem
2012
Published version of a chapter in the book: Advanced Research in Applied Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-31087-4_78 This paper deals with the Stochastic-Point Location (SPL) problem. It presents a solution which is novel in both philosophy and strategy to all the reported related learning algorithms. The SPL problem concerns the task of a Learning Mechanism attempting to locate a point on a line. The mechanism interacts with a random environment which essentially informs it, possibly erroneously, if the unknown parameter is on the left or the right of a given point which also is the current guess. The first pioneering work […
Learning automata-based solutions to the optimal web polling problem modelled as a nonlinear fractional knapsack problem
2011
We consider the problem of polling web pages as a strategy for monitoring the world wide web. The problem consists of repeatedly polling a selection of web pages so that changes that occur over time are detected. In particular, we consider the case where we are constrained to poll a maximum number of web pages per unit of time, and this constraint is typically dictated by the governing communication bandwidth, and by the speed limitations associated with the processing. Since only a fraction of the web pages can be polled within a given unit of time, the issue at stake is one of determining which web pages are to be polled, and we attempt to do it in a manner that maximizes the number of ch…
Alignment-free sequence comparison using absent words
2018
Sequence comparison is a prerequisite to virtually all comparative genomic analyses. It is often realised by sequence alignment techniques, which are computationally expensive. This has led to increased research into alignment-free techniques, which are based on measures referring to the composition of sequences in terms of their constituent patterns. These measures, such as $q$-gram distance, are usually computed in time linear with respect to the length of the sequences. In this paper, we focus on the complementary idea: how two sequences can be efficiently compared based on information that does not occur in the sequences. A word is an {\em absent word} of some sequence if it does not oc…
Weakly coupled map lattice models for multicellular patterning and collective normalization of abnormal single-cell states
2017
We present a weakly coupled map lattice model for patterning that explores the effects exerted by weakening the local dynamic rules on model biological and artificial networks composed of two-state building blocks (cells). To this end, we use two cellular automata models based on: (i) a smooth majority rule (model I) and (ii) a set of rules similar to those of Conway's Game of Life (model II). The normal and abnormal cell states evolve according with local rules that are modulated by a parameter $\kappa$. This parameter quantifies the effective weakening of the prescribed rules due to the limited coupling of each cell to its neighborhood and can be experimentally controlled by appropriate e…
A Novel Tsetlin Automata Scheme to Forecast Dengue Outbreaks in the Philippines
2018
Being capable of online learning in unknown stochastic environments, Tsetlin Automata (TA) have gained considerable interest. As a model of biological systems, teams of TA have been used for solving complex problems in a decentralized manner, with low computational complexity. For many domains, decentralized problem solving is an advantage, however, also may lead to coordination difficulties and unstable learning. To combat this negative effect, this paper proposes a novel TA coordination scheme designed for learning problems with continuous input and output. By saving and updating the best solution that has been chosen so far, we can avoid having the overall system being led astray by spur…
A detailed experimental study of a DNA computer with two endonucleases
2017
Abstract Great advances in biotechnology have allowed the construction of a computer from DNA. One of the proposed solutions is a biomolecular finite automaton, a simple two-state DNA computer without memory, which was presented by Ehud Shapiro’s group at the Weizmann Institute of Science. The main problem with this computer, in which biomolecules carry out logical operations, is its complexity – increasing the number of states of biomolecular automata. In this study, we constructed (in laboratory conditions) a six-state DNA computer that uses two endonucleases (e.g. AcuI and BbvI) and a ligase. We have presented a detailed experimental verification of its feasibility. We described the effe…
Novel Distance Estimation Methods Using 'Stochastic Learning on the Line' Strategies
2018
In this paper, we consider the problem of Distance Estimation (DE) when the inputs are the $x$ and $y$ coordinates (or equivalently, the latitudinal and longitudinal positions) of the points under consideration. The aim of the problem is to yield an accurate value for the real (road) distance between the points specified by the latter coordinates. 1 This problem has, typically, been tackled by utilizing parametric functions called the “Distance Estimation Functions” (DEFs). The parameters are learned from the training data (i.e., the true road distances) between a subset of the points under consideration. We propose to use Learning Automata (LA)-based strategies to solve the problem. In par…
Learning automata based energy-efficient AI hardware design for IoT applications
2020
Energy efficiency continues to be the core design challenge for artificial intelligence (AI) hardware designers. In this paper, we propose a new AI hardware architecture targeting Internet of Things applications. The architecture is founded on the principle of learning automata, defined using propositional logic. The logic-based underpinning enables low-energy footprints as well as high learning accuracy during training and inference, which are crucial requirements for efficient AI with long operating life. We present the first insights into this new architecture in the form of a custom-designed integrated circuit for pervasive applications. Fundamental to this circuit is systematic encodin…
Un cuento de robots : La hija cibernética de descartes
2021
French philosopher René Descartes is today valued as a forerunner of the studies of human mind, artificial intelligence and robotic systems. Throughout his work there are large references to automata and the possibility of artificial life, as well as an assessment of the differences between rational behavior of human beings and the purely mechanical of animals and automata. In addition to these references, there is a fable about the creation by the philosopher of an automaton that replicated his deceased daughter Francine, a story that is well known among the French and Anglo-Saxon specialists, but not so much in the Spanish ones, which is what settles this short work