A systematic study of probabilistic aggregation strategies in swarm robotic systems

Download

index.pdf

Date

2005

Author

Soysal, Onur

Metadata

Show full item record

Item Usage Stats

345
views

102
downloads

In this study, a systematic analysis of probabilistic aggregation strategies in swarm robotic systems is presented. A generic aggregation behavior is proposed as a combination of four basic behaviors: obstacle avoidance, approach, repel, and wait. The latter three basic behaviors are combined using a three-state finite state machine with two probabilistic transitions among them. Two different metrics were used to compare performance of strategies. Through systematic experiments, how the aggregation performance, as measured by these two metrics, change 1) with transition probabilities, 2) with number of simulation steps, and 3) with arena size, is studied.

Subject Keywords

Computer software.

URI

http://etd.lib.metu.edu.tr/upload/12606460/index.pdf
https://hdl.handle.net/11511/15360

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Modelling and predicting binding affinity of PCP-like compounds using machine learning methods Erdaş, Özlem; Alpaslan, Ferda Nur; Department of Computer Engineering (2007) Machine learning methods have been promising tools in science and engineering fields. The use of these methods in chemistry and drug design has advanced after 1990s. In this study, molecular electrostatic potential (MEP) surfaces of PCP-like compounds are modelled and visualized in order to extract features which will be used in predicting binding affinity. In modelling, Cartesian coordinates of MEP surface points are mapped onto a spherical self-organizing map. Resulting maps are visualized by using values...
Analysis of extended feature models with constraint programming Karataş, Ahmet Serkan; Oğuztüzün, Mehmet Halit S.; Department of Computer Engineering (2010) In this dissertation we lay the groundwork of automated analysis of extended feature models with constraint programming. Among different proposals, feature modeling has proven to be very effective for modeling and managing variability in Software Product Lines. However, industrial experiences showed that feature models often grow too large with hundreds of features and complex cross-tree relationships, which necessitates automated analysis support. To address this issue we present a mapping from extended fe...
A classification system for the problem of protein subcellular localization Alay, Gökçen; Atalay, Mehmet Volkan; Department of Computer Engineering (2007) The focus of this study is on predicting the subcellular localization of a protein. Subcellular localization information is important for protein function annotation which is a fundamental problem in computational biology. For this problem, a classification system is built that has two main parts: a predictor that is based on a feature mapping technique to extract biologically meaningful information from protein sequences and a client/server architecture for searching and predicting subcellular localization...
Special index and retrieval mechanism for ontology based medical domain search engines Kubilay, Mustafa; Baykal, Nazife; Department of Information Systems (2005) This thesis focuses on index and retrieval mechanism of an ontology based medical domain search engine. First, indexing techniques and retrieval methods are reviewed. Then, a special indexing and retrieval mechanism are introduced. This thesis also specifies the functional requirements of these mechanisms. Finally, an evaluation is given by indicating the positive and negative aspects of mechanisms.
A clustering method for the problem of protein subcellular localization Bezek, Perit; Atalay, Mehmet Volkan; Department of Computer Engineering (2006) In this study, the focus is on predicting the subcellular localization of a protein, since subcellular localization is helpful in understanding a protein’s functions. Function of a protein may be estimated from its sequence. Motifs or conserved subsequences are strong indicators of function. In a given sample set of protein sequences known to perform the same function, a certain subsequence or group of subsequences should be common; that is, occurrence (frequency) of common subsequences should be high. Our ...

Citation Formats

O. Soysal, “A systematic study of probabilistic aggregation strategies in swarm robotic systems,” M.S. - Master of Science, Middle East Technical University, 2005.