Search results for "Automaton"
showing 10 items of 257 documents
A Short Presentation of LucSim
2017
LucSim is a cellular automata (CA) dedicated to geographical analysis and spatial simulation for researchers and advanced planning institutes, providing user-friendly software in order to analyze and simulate land use changes and dynamics. Two complementary models are integrated in the CA: (1) a Markov Chain used to calculate transition matrices from a date to another, and (2) a Decision Tree able to automatically determine a set of transition rules to be applied on land use data. LucSim includes GIS compatibility functions allowing to display ESRI shapefiles and is based on raster georeferenced images saved in TIF format. It was mostly applied on French urban case studies.
Towards a Theory of Life
2015
In this paper, I set out the contributions made by some European biologists, as well as other more heterodox ones, to the recent development of theoretical thinking in biology. Theoretical biology is a relatively new discipline when compared with theoretical physics, in part because the formal languages of logic and computing which it uses have only emerged recently. Finally, I suggest that in order to build a theory of life we need to combine a cell theory based on a proper description of the laws that map the genotype in the phenotype and vice versa with the laws of evolution. Only then will we be able to properly explain the transformation and complexity of living things.
A challenging family of automata for classical minimization algorithms
2010
In this paper a particular family of deterministic automata that was built to reach the worst case complexity of Hopcroft's state minimization algorithm is considered. This family is also challenging for the two other classical minimization algorithms: it achieves the worst case for Moore's algorithm, as a consequence of a result by Berstel et al., and is of at least quadratic complexity for Brzozowski's solution, which is our main contribution. It therefore constitutes an interesting family, which can be useful to measure the efficiency of implementations of well-known or new minimization algorithms.
On Using a Hierarchy of Twofold Resource Allocation Automata to Solve Stochastic Nonlinear Resource Allocation Problems
2007
Recent trends in AI attempt to solve difficult NP-hard problems using intelligent techniques so as to obtain approximately-optimal solutions. In this paper, we consider a family of such problems which fall under the general umbrella of "knapsack-like" problems, and demonstrate how we can solve all of them fast and accurately using a hierarchy of Learning Automata (LA). In a multitude of real-world situations, resources must be allocated based on incomplete and noisy information, which often renders traditional resource allocation techniques ineffective. This paper addresses one such class of problems, namely, Stochastic Non-linear Fractional Knapsack Problems. We first present a completely …
Achieving Fair Load Balancing by Invoking a Learning Automata-Based Two-Time-Scale Separation Paradigm.
2020
Author's accepted manuscript. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. In this article, we consider the problem of load balancing (LB), but, unlike the approaches that have been proposed earlier, we attempt to resolve the problem in a fair manner (or rather, it would probably be more appropriate to describe it as an ε-fair manner because, although the LB…
The Power of the “Pursuit” Learning Paradigm in the Partitioning of Data
2019
Traditional Learning Automata (LA) work with the understanding that the actions are chosen purely based on the “state” in which the machine is. This modus operandus completely ignores any estimation of the Random Environment’s (RE’s) (specified as \(\mathbb {E}\)) reward/penalty probabilities. To take these into consideration, Estimator/Pursuit LA utilize “cheap” estimates of the Environment’s reward probabilities to make them converge by an order of magnitude faster. This concept is quite simply the following: Inexpensive estimates of the reward probabilities can be used to rank the actions. Thereafter, when the action probability vector has to be updated, it is done not on the basis of th…
Modeling urban growth by cellular automata
1996
International audience; The structural development of human settlements can be characterized as a complex highly feedbacketed process. The assumption that this process is governed by rather few fundamental laws stimulated a considerable research in the field of urban growth during the last decade. Aiming at the comprehension of the basic underlying dynamics different approaches from the field of self-organizing systems have been proposed. In this paper we present a "cellular model" of urban growth dynamics based on the work of White, Engelen and Uljee. As a starting point this model throws some light on the mechanism of urban growth. But even more important, it raises a lot of questions con…
Complex Adaptive Systems and Agent-Based Modelling
2015
In a labour–education market system, there are many individuals and firms with adaptive behaviour. As we have seen in the previous chapter, networks are prevalent in LEMS and play an important role in many decisions of its actors. Thus, LEMS can be analysed as a complex adaptive system (CAS). Agent-based modelling (ABM) is typically used for such purposes, and the next chapter will dig into details of various ways of applying ABM in modelling LEMS. To be ready for it, we first have to understand the motivation behind and the details of this method. This is what will be discussed here.
Verification of Well-Formed Communicating Recursive State Machines
2008
AbstractIn this paper we introduce a new (non-Turing equivalent) formal model of recursive concurrent programs called well-formed communicating recursive state machines (CRSM). CRSM extend recursive state machines (RSM) by allowing a restricted form of concurrency: a state of a module can be refined into a finite collection of modules (working in parallel) in a potentially recursive manner. Communication is only possible between the activations of modules invoked on the same fork. We study the model-checking problem of CRSM with respect to specifications expressed in a temporal logic that extends CaRet with a parallel operator (ConCaRet). We propose a decision algorithm that runs in time ex…
Minimal Büchi Automata for Certain Classes of LTL Formulas
2009
In this paper we calculate the minimal number of states of Buchi automata which encode some classes of linear temporal logic (LTL) formulas that are frequently used in model checking. Our results may be used for verification of the quality of algorithms which automatically translate LTL formulas into Buchi automata and for improving the quality and speed of such translators. In the last section of this paper we compare our lower-bound estimations to Buchi automata generated by two currently used translators: LTL2BA and SPOT.