Search results for " programmi"
showing 10 items of 1629 documents
Soft Pyramid Symmetry Transforms
2005
Pyramid computation is a natural paradigm of computation in planning strategies and multi-resolution image analysis. This paper introduces a new paradigm that is based on the concept of soft-hierarchical operators implemented in a pyramid architecture to retrieve global versus local symmetries. The concept of symmetry is mathematically well defined in geometry whenever patterns are crisp images (two levels). Necessity for a soft approach occurs whenever images are multi-levels and the separation between object and background is subjective or not well defined. The paper describes a new pyramid operator to detect symmetries and shows some experiments supporting the approach. This work has bee…
The Hierarchical Continuous Pursuit Learning Automation: A Novel Scheme for Environments With Large Numbers of Actions.
2019
Although the field of learning automata (LA) has made significant progress in the past four decades, the LA-based methods to tackle problems involving environments with a large number of actions is, in reality, relatively unresolved. The extension of the traditional LA to problems within this domain cannot be easily established when the number of actions is very large. This is because the dimensionality of the action probability vector is correspondingly large, and so, most components of the vector will soon have values that are smaller than the machine accuracy permits, implying that they will never be chosen . This paper presents a solution that extends the continuous pursuit paradigm to …
The Hierarchical Continuous Pursuit Learning Automation for Large Numbers of Actions
2018
Part 10: Learning - Intelligence; International audience; Although the field of Learning Automata (LA) has made significant progress in the last four decades, the LA-based methods to tackle problems involving environments with a large number of actions are, in reality, relatively unresolved. The extension of the traditional LA (fixed structure, variable structure, discretized, and pursuit) to problems within this domain cannot be easily established when the number of actions is very large. This is because the dimensionality of the action probability vector is correspondingly large, and consequently, most components of the vector will, after a relatively short time, have values that are smal…
Challenges of Program Synthesis with Grammatical Evolution
2020
Program synthesis is an emerging research topic in the field of EC with the potential to improve real-world software development. Grammar-guided approaches like GE are suitable for program synthesis as they can express common programming languages with their required properties. This work uses common software metrics (lines of code, McCabe metric, size and depth of the abstract syntax tree) for an analysis of GE’s search behavior and the resulting problem structure. We find that GE is not able to solve program synthesis problems, where correct solutions have higher values of the McCabe metric (which means they require conditions or loops). Since small mutations of high-quality solutions str…
Diagrammatic approach to cellular automata and the emergence of form with inner structure
2018
We present a diagrammatic method to build up sophisticated cellular automata (CAs) as models of complex physical systems. The diagrams complement the mathematical approach to CA modeling, whose details are also presented here, and allow CAs in rule space to be classified according to their hierarchy of layers. Since the method is valid for any discrete operator and only depends on the alphabet size, the resulting conclusions, of general validity, apply to CAs in any dimension or order in time, arbitrary neighborhood ranges and topology. We provide several examples of the method, illustrating how it can be applied to the mathematical modeling of the emergence of order out of disorder. Specif…
Representations for evolutionary algorithms
2015
Successful and efficient use of evolutionary algorithms (EA) depends on the choice of the genotype, the problem representation (mapping from genotype to phenotype) and on the choice of search operators that are applied to the genotypes. These choices cannot be made independently of each other. The question whether a certain representation leads to better performing EAs than an alternative representation can only be answered when the operators applied are taken into consideration. The reverse is also true: deciding between alternative operators is only meaningful for a given representation. In EA practice one can distinguish two complementary approaches. The first approach uses indirect repr…
High Locality Representations for Automated Programming
2011
We study the locality of the genotype-phenotype mapping used in grammatical evolution (GE). GE is a variant of genetic programming that can evolve complete programs in an arbitrary language using a variable-length binary string. In contrast to standard GP, which applies search operators directly to phenotypes, GE uses an additional mapping and applies search operators to binary genotypes. Therefore, there is a large semantic gap between genotypes (binary strings) and phenotypes (programs or expressions). The case study shows that the mapping used in GE has low locality leading to low performance of standard mutation operators. The study at hand is an example of how basic design principles o…
LeSSS: Learned Shared Semantic Spaces for Relating Multi-Modal Representations of 3D Shapes
2015
In this paper, we propose a new method for structuring multi-modal representations of shapes according to semantic relations. We learn a metric that links semantically similar objects represented in different modalities. First, 3D-shapes are associated with textual labels by learning how textual attributes are related to the observed geometry. Correlations between similar labels are captured by simultaneously embedding labels and shape descriptors into a common latent space in which an inner product corresponds to similarity. The mapping is learned robustly by optimizing a rank-based loss function under a sparseness prior for the spectrum of the matrix of all classifiers. Second, we extend …
A Logic of Discovery
1998
A logic of discovery is introduced. In this logic, true sentences are discovered over time based on arriving data. A notion of expectation is introduced to reflect the growing certainty that a universally quantified sentence is true as more true instances are observed. The logic is shown to be consistent and complete. Monadic predicates are considered as a special case
Consensus in Noncooperative Dynamic Games: a Multi-Retailer Inventory Application
2008
We focus on Nash equilibria and Pareto optimal Nash equilibria for a finite horizon noncooperative dynamic game with a special structure of the stage cost. We study the existence of these solutions by proving that the game is a potential game. For the single-stage version of the game, we characterize the aforementioned solutions and derive a consensus protocol that makes the players converge to the unique Pareto optimal Nash equilibrium. Such an equilibrium guarantees the interests of the players and is also social optimal in the set of Nash equilibria. For the multistage version of the game, we present an algorithm that converges to Nash equilibria, unfortunately, not necessarily Pareto op…