Characterization of rational and algebraic power series
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Classification and clustering of printed mathematical symbols with improved backpropagation and self-organizing map.
Classification of reduction invariants with improved backpropagation.
Classification results in quasigroup and loop theory via a combination of automated reasoning tools
We present some novel classification results in quasigroup and loop theory. For quasigroups up to size 5 and loops up to size 7, we describe a unique property which determines the isomorphism (and in the case of loops, the isotopism) class for any example. These invariant properties were generated using a variety of automated techniques --- including machine learning and computer algebra --- which we present here. Moreover, each result has been automatically verified, again using a variety of techniques...
Classification Trees as a Technique for Creating Anomaly-Based Intrusion Detection Systems
Intrusion detection is a critical component of security information systems. The intrusion detection process attempts to detect malicious attacks by examining various data collected during processes on the protected system. This paper examines the anomaly-based intrusion detection based on sequences of system calls. The point is to construct a model that describes normal or acceptable system activity using the classification trees approach. The created database is utilized as a basis for distinguishing...
Closed sets of universal Horn formulas for many-sorted (partial) algebras
Clustering of vaguely defined objects
This paper is concerned with the clustering of objects whose properties cannot be described by exact data. These can only be described by fuzzy sets or by linguistic values of previously defined linguistic variables. To cluster these objects we use a generalization of classic clustering methods in which instead of similarity (dissimilarity) of objects, used fuzzy similarity (fuzzy dissimilarity) to define the clustering of fuzzy objects.
Cocktail: a tool for deriving correct programs.
Cocktail is a tool for deriving correct programs from their specifications. The present version is powerful enough for educational purposes. The tool yields support for many sorted first order predicate logic, formulated in a pure type system with parametric constants (CPTS), as the specification language, a simple While-language, a Hoare logic represented in the same CPTS for deriving programs from their specifications and a simple tableau based automated theorem prover for verifying proof obligations....
Codes avec des mots infinis
Coevolutionary genetic algorithms for establishing Nash equilibrium in symmetric Cournot games.
Cognitive psychology and artificial intelligence
Coherence principles for handling qualitative and quantitative partial probabilistic assessments.
In this paper we present an overview of mathematical models for handling partial entailments and their extensions in a probabilistic frame.
Combination of mobile agent and evolutionary algorithm to optimize the client transport services
This paper presents a migration strategy for a set of mobile agents (MAs) in order to satisfy customers' requests in a transport network, through a multimodal information system. In this context, we propose an optimization solution which operates on two levels. The first one aims to constitute a set of MAs building their routes, called Workplans. At this level, Workplans must incorporate all nodes, representing information providers in the multimodal network, in order to explore it completely....
Combining adaptive vector quantization and prototype selection techniques to improve nearest neighbour classifiers
Prototype Selection (PS) techniques have traditionally been applied prior to Nearest Neighbour (NN) classification rules both to improve its accuracy (editing) and to alleviate its computational burden (condensing). Methods based on selecting/discarding prototypes and methods based on adapting prototypes have been separately introduced to deal with this problem. Different approaches to this problem are considered in this paper and their main advantages and drawbacks are pointed out along with some...
Combining biometric fractal pattern and particle swarm optimization-based classifier for fingerprint recognition.
Combining constraint Propagation and meta-heuristics for searching a Maximum Weight Hamiltonian Chain
This paper presents the approach that we developed to solve the ROADEF 2003 challenge problem. This work is part of a research program whose aim is to study the benefits and the computer-aided generation of hybrid solutions that mix constraint programming and meta-heuristics, such as large neighborhood search (LNS). This paper focuses on three contributions that were obtained during this project: an improved method for propagating Hamiltonian chain constraints, a fresh look at limited discrepancy...
Combining odometry and visual loop-closure detection for consistent topo-metrical mapping
We address the problem of simultaneous localization and mapping (SLAM) by combining visual loop-closure detection with metrical information given by a robot odometry. The proposed algorithm extends a purely appearance-based loop-closure detection method based on bags of visual words [A. Angeli, D. Filliat, S. Doncieux and J.-A. Meyer, IEEE Transactions On Robotics, Special Issue on Visual SLAM 24 (2008) 1027–1037], which is able to detect when the robot has returned back to a previously visited...
Combining Odometry and Visual Loop-Closure Detection for Consistent Topo-Metrical Mapping
We address the problem of simultaneous localization and mapping (SLAM) by combining visual loop-closure detection with metrical information given by a robot odometry. The proposed algorithm extends a purely appearance-based loop-closure detection method based on bags of visual words [A. Angeli, D. Filliat, S. Doncieux and J.-A. Meyer, IEEE Transactions On Robotics, Special Issue on Visual SLAM24 (2008) 1027–1037], which is able to detect when the robot has returned back to a previously visited...
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