Search results for "Automaton"
showing 10 items of 257 documents
Mining Interpretable Rules for Sentiment and Semantic Relation Analysis Using Tsetlin Machines
2020
Tsetlin Machines (TMs) are an interpretable pattern recognition approach that captures patterns with high discriminative power from data. Patterns are represented as conjunctive clauses in propositional logic, produced using bandit-learning in the form of Tsetlin Automata. In this work, we propose a TM-based approach to two common Natural Language Processing (NLP) tasks, viz. Sentiment Analysis and Semantic Relation Categorization. By performing frequent itemset mining on the patterns produced, we show that they follow existing expert-verified rule-sets or lexicons. Further, our comparison with other widely used machine learning techniques indicates that the TM approach helps maintain inter…
A Formal Semantics and a Client Synthesis for a BPEL Service
2008
A complex Web service described with languages like BPEL4WS, consists of an executable process and its observable behaviour (called an abstract process) based on the messages exchanged with the client. The abstract process behaviour is non deterministic due to the internal choices during the service execution. Furthermore the specification often includes timing constraints which must be taken into account by the client. Thus given a service specification, we identify the synthesis of a client as a key issue for the development of Web services. To this end, we propose an approach based on (dense) timed automata to first describe the observable service behaviour and then to build correct inte…
Iterative pairs and multitape automata
1996
In this paper we prove that if every iterative k-tuple of a language L recognized by a k-tape automaton is very degenerate, then L is recognizable. Moreover, we prove that if L is an aperiodic langnage recognized by a deterministic k-tape automaton, then L is recognizable.
A generic model of reinforcement learning combined with macroscopic cellular automata to simulate land use change
2019
Better understanding the evolution of land cover is a priority concern in the field of land use change study. This evolution can be the result of interactions between major factors. The study of land use change is included in territorial planning to inform planners and policy makers of possible developments they will face. Land use models are useful for reasonable land use management to optimize future land management decisions. In this paper we present an original theoretical model of reinforcement learning combined with macroscopic cellular automata to simulate land use change.
Speeding up of microstructure reconstruction: II. Application to patterns of poly-dispersed islands
2015
We report a fast, efficient and credible statistical reconstruction of any two-phase patterns of islands of miscellaneous shapes and poly-dispersed in sizes. In the proposed multi-scale approach called a weighted doubly-hybrid, two different pairs of hybrid descriptors are used. As the first pair, we employ entropic quantifiers, while correlation functions are the second pair. Their competition allows considering a wider spectrum of morphological features. Instead of a standard random initial configuration, a synthetic one with the same number of islands as that of the target is created by a cellular automaton. This is the key point for speeding-up of microstructure reconstruction, making u…
Speeding up of microstructure reconstruction: I. Application to labyrinth patterns
2011
Recently, entropic descriptors based the Monte Carlo hybrid reconstruction of the microstructure of a binary/greyscale pattern has been proposed (Piasecki 2011 Proc. R. Soc. A 467 806). We try to speed up this method applied in this instance to the reconstruction of a binary labyrinth target. Instead of a random configuration, we propose to start with a suitable synthetic pattern created by cellular automaton. The occurrence of the characteristic attributes of the target is the key factor for reducing the computational cost that can be measured by the total number of MC steps required. For the same set of basic parameters, we investigated the following simulation scenarios: the biased/rando…
A Learning-Automata Based Solution for Non-equal Partitioning: Partitions with Common GCD Sizes
2021
The Object Migration Automata (OMA) has been used as a powerful tool to resolve real-life partitioning problems in random Environments. The virgin OMA has also been enhanced by incorporating the latest strategies in Learning Automata (LA), namely the Pursuit and Transitivity phenomena. However, the single major handicap that it possesses is the fact that the number of objects in each partition must be equal. Obviously, one does not always encounter problems with equally-sized groups (When the true underlying problem has non-equally-sized groups, the OMA reports the best equally-sized solution as the recommended partition.). This paper is the pioneering attempt to relax this constraint. It p…
Learning-automaton-based online discovery and tracking of spatiotemporal event patterns.
2013
Discovering and tracking of spatiotemporal patterns in noisy sequences of events are difficult tasks that have become increasingly pertinent due to recent advances in ubiquitous computing, such as community-based social networking applications. The core activities for applications of this class include the sharing and notification of events, and the importance and usefulness of these functionalities increase as event sharing expands into larger areas of one's life. Ironically, instead of being helpful, an excessive number of event notifications can quickly render the functionality of event sharing to be obtrusive. Indeed, any notification of events that provides redundant information to the…
Automated Synthesis of Application-layer Connectors from Automata-based Specifications
2019
Abstract Ubiquitous and Pervasive Computing, and the Internet of Things, promote dynamic interaction among heterogeneous systems. To achieve this vision, interoperability among heterogeneous systems represents a key enabler, and mediators are often built to solve protocol mismatches. Many approaches propose the synthesis of mediators. Unfortunately, a rigorous characterization of the concept of interoperability is still lacking, hence making hard to assess their applicability and soundness. In this paper, we provide a framework for the synthesis of mediators that allows us to: (i) characterize the conditions for the mediator existence and correctness; and (ii) establish the applicability bo…
One-Counter Verifiers for Decidable Languages
2013
Condon and Lipton (FOCS 1989) showed that the class of languages having a space-bounded interactive proof system (IPS) is a proper subset of decidable languages, where the verifier is a probabilistic Turing machine. In this paper, we show that if we use architecturally restricted verifiers instead of restricting the working memory, i.e. replacing the working tape(s) with a single counter, we can define some IPS’s for each decidable language. Such verifiers are called two-way probabilistic one-counter automata (2pca’s). Then, we show that by adding a fixed-size quantum memory to a 2pca, called a two-way one-counter automaton with quantum and classical states (2qcca), the protocol can be spac…