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- Answer set programming (9)
- Security (7)
- Internet of things (6)
- Privacy (4)
- Propositional satisfiability (3)
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- Wearables (3)
- Bystanders' privacy (2)
- COVID-19 (2)
- Crowd simulation (2)
- Crowdsensing (2)
- Data clustering (2)
- Data mining (2)
- Face detection (2)
- Face recognition (2)
- Gene expression profiling (2)
- Hierarchical collective agent network (2)
- Internet of Things (2)
- Knowledge representation (2)
- Location-based services (2)
- Logic programming methodology and applications (2)
- Loop formulas (2)
- Participatory sensing (2)
- Pattern classification (2)
- SAT (2)
- Sensing (2)
- Specification (2)
- Subgoal learning (2)
- Technical paper (2)
- Theory (2)
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Articles 31 - 60 of 77
Full-Text Articles in Physical Sciences and Mathematics
On Abstract Modular Inference Systems And Solvers, Yuliya Lierler, Miroslaw Truszczyński
On Abstract Modular Inference Systems And Solvers, Yuliya Lierler, Miroslaw Truszczyński
Computer Science Faculty Publications
Integrating diverse formalisms into modular knowledge representation systems offers increased expressivity, modeling convenience, and computational benefits. We introduce the concepts of abstract inference modules and abstract modular inference systems to study general principles behind the design and analysis of model generating programs, or solvers, for integrated multi-logic systems. We show how modules and modular systems give rise to transition graphs, which are a natural and convenient representation of solvers, an idea pioneered by the SAT community. These graphs lend themselves well to extensions that capture such important solver design features as learning. In the paper, we consider two …
Training Learnings To Self-Explains: Designing Instructions And Examples To Improve Problem Solving, Lauren E. Margulieux, Briana B. Morrison, Richard Catrambone
Training Learnings To Self-Explains: Designing Instructions And Examples To Improve Problem Solving, Lauren E. Margulieux, Briana B. Morrison, Richard Catrambone
Computer Science Faculty Publications
In this experiment, we integrated two learning methods – subgoal learning and constructive learning – to explore their interactions and effects on solving computer programming problems. We taught learners to solve problems using worked example and practice problem pairs with one of three kinds of instructional design that either did not highlight the subgoals, described the subgoals, or prompted participants to describe the subgoals for themselves. In addition, we varied the distance of transfer between the worked example and practice problem pairs. We found that instructions that highlighted subgoals improved performance on later problem solving tasks. The groups that performed …
Graph Mining For Next Generation Sequencing: Leveraging The Assembly Graph For Biological Insights, Julia Warnke-Sommer, Hesham Ali
Graph Mining For Next Generation Sequencing: Leveraging The Assembly Graph For Biological Insights, Julia Warnke-Sommer, Hesham Ali
Computer Science Faculty Publications
Background: The assembly of Next Generation Sequencing (NGS) reads remains a challenging task. This is especially true for the assembly of metagenomics data that originate from environmental samples potentially containing hundreds to thousands of unique species. The principle objective of current assembly tools is to assemble NGS reads into contiguous stretches of sequence called contigs while maximizing for both accuracy and contig length. The end goal of this process is to produce longer contigs with the major focus being on assembly only. Sequence read assembly is an aggregative process, during which read overlap relationship information is lost as reads are …
Near-Duplicate Image Retrieval Based On Contextual Descriptor, Jinliang Yao, Bing Yang, Qiuming Zhu
Near-Duplicate Image Retrieval Based On Contextual Descriptor, Jinliang Yao, Bing Yang, Qiuming Zhu
Computer Science Faculty Publications
The state of the art of technology for near-duplicate image retrieval is mostly based on the Bag-of-Visual-Words model. However, visual words are easy to result in mismatches because of quantization errors of the local features the words represent. In order to improve the precision of visual words matching, contextual descriptors are designed to strengthen their discriminative power and measure the contextual similarity of visual words. This paper presents a new contextual descriptor that measures the contextual similarity of visual words to immediately discard the mismatches and reduce the count of candidate images. The new contextual descriptor encodes the relationships of …
A Specific Type Of Cyclin-Like F-Box Domain Gene Is Involved In The Cryogenic Autolysis Of Volvariella Volvacea, Ming Gong, Mingjie Chen, Hong Wang, Qiuming Zhu, Qi Tan
A Specific Type Of Cyclin-Like F-Box Domain Gene Is Involved In The Cryogenic Autolysis Of Volvariella Volvacea, Ming Gong, Mingjie Chen, Hong Wang, Qiuming Zhu, Qi Tan
Computer Science Faculty Publications
Cryogenic autolysis is a typical phenomenon of abnormal metabolism in Volvariella volvacea. Recent studies have identified 20 significantly upregulated genes via high-throughput sequencing of the mRNAs expressed in the mycelia of V. volvacea after cold exposure. Among these significantly upregulated genes, 15 annotated genes were used for functional annotation cluster analysis. Our results showed that the cyclin-like F-box domain (FBDC) formed the functional cluster with the lowest P-value. We also observed a significant expansion of FBDC families in V. volvacea. Among these, the FBDC3 family displayed the maximal gene expansion in V. volvacea. Gene expression profiling analysis revealed …
Optimal Acceleration Thresholds For Non-Holonomic Agents, Brian Ricks, Parris K. Egbert
Optimal Acceleration Thresholds For Non-Holonomic Agents, Brian Ricks, Parris K. Egbert
Computer Science Faculty Publications
Finding optimal trajectories for non-accelerating, non-holonomic agents is a well-understood problem. However, in video games, robotics, and crowd simulations non-holonomic agents start and stop frequently. With the vision of improving crowd simulation, we find optimal paths for virtual agents accelerating from a standstill. These paths are designed for the “ideal”, initial stage of planning when obstacles are ignored. We analytically derive paths and arrival times using arbitrary acceleration angle thresholds. We use these paths and arrival times to find an agent’s optimal ideal path. We then numerically calculate the decision surface that can be used by an application at run-time …
Relating Constraint Answer Set Programming Languages And Algorithms, Yuliya Lierler
Relating Constraint Answer Set Programming Languages And Algorithms, Yuliya Lierler
Computer Science Faculty Publications
Recently a logic programming language AC was proposed by Mellarkod et al. (2008) to integrate answer set programming and constraint logic programming. Soon after that, a CLINGCON language integrating answer set programming and finite domain constraints, as well as an EZCSP language integrating answer set programming and constraint logic programming were introduced. The development of these languages and systems constitutes the appearance of a new AI subarea called constraint answer set programming. All these languages have something in common. In particular, they aim at developing new efficient inference algorithms that combine traditional answer set programming procedures and other methods in …
Deliberate Barriers To User Participation On Metafilter, Hannah Pileggi, Briana B. Morrison, Amy Bruckman
Deliberate Barriers To User Participation On Metafilter, Hannah Pileggi, Briana B. Morrison, Amy Bruckman
Computer Science Faculty Publications
This descriptive study explores deliberate barriers to user participation on the long-lived discussion site Metafilter.com. Metafilter has been in continuous operation since its founding in 1999, and at the time of this writing has around 12,000 active users. While many newer online sites appear eager to eliminate barriers to participation and recruit as many new members as possible, Metafilter charges a $5 fee to join and has a mandatory one-week waiting period before new users are allowed to post. In this paper, we explore both why these barriers were imposed and why some users choose to surmount the barriers to …
A Social Dimensional Cyber Threat Model With Formal Concept Analysis And Fact-Proposition Inference, Anup Sharma, Robin Gandhi, Qiuming Zhu, William Mahoney, William Sousan
A Social Dimensional Cyber Threat Model With Formal Concept Analysis And Fact-Proposition Inference, Anup Sharma, Robin Gandhi, Qiuming Zhu, William Mahoney, William Sousan
Computer Science Faculty Publications
Cyberspace has increasingly become a medium to express outrage, conduct protests, take revenge, spread opinions, and stir up issues. Many cyber attacks can be linked to current and historic events in the social, political, economic, and cultural (SPEC) dimensions of human conflicts in the physical world. These SPEC factors are often the root cause of many cyber attacks. Understanding the relationships between past and current SPEC events and cyber attacks can help understand and better prepare people for impending cyber attacks. The focus of this paper is to analyze these attacks in social dimensions and build a threat model based …
Integration Schemas For Constraint Answer Set Programming: A Case Study, Marcello Balduccini, Yuliya Lierler
Integration Schemas For Constraint Answer Set Programming: A Case Study, Marcello Balduccini, Yuliya Lierler
Computer Science Faculty Publications
Recently, researchers in answer set programming and constraint programming spent significant efforts in the development of hybrid languages and solving algorithms combining the strengths of these traditionally separate fields. These efforts resulted in a new research area: constraint answer set programming (CASP). CASP languages and systems proved to be largely successful at providing efficient solutions to problems involving hybrid reasoning tasks, such as scheduling problems with elements of planning. Yet, the development of CASP systems is difficult, requiring non-trivial expertise in multiple areas. This suggests a need for a study identifying general development principles of hybrid systems. Once these principles …
Constraint Answer Set Programming, Yuliya Lierler
Constraint Answer Set Programming, Yuliya Lierler
Computer Science Faculty Publications
Constraint answer set programming (CASP) is a novel, promising direction of research whose roots go back to propositional satisfiability (SAT). SAT solvers are efficient tools for solving boolean constraint satisfaction problems that arise in different areas of computer science, including software and hardware verification. Some constraints are more naturally expressed by non-boolean constructs. Satisfiability modulo theories (SMT) extends boolean satisfiability by the integration of non-boolean symbols defined by a background theory in another formalism, such as a constraint processing language. Answer set programming (ASP) extends computational methods of SAT in yet another way, inspired by ideas from knowledge representation, logic …
Representing First-Order Causal Theories By Logic Programs, Paolo Ferrarris, Joohyung Lee, Yuliya Lierler, Vladimir Lifschitz, Fangkai Yang
Representing First-Order Causal Theories By Logic Programs, Paolo Ferrarris, Joohyung Lee, Yuliya Lierler, Vladimir Lifschitz, Fangkai Yang
Computer Science Faculty Publications
Nonmonotonic causal logic, introduced by McCain and Turner (McCain, N. and Turner, H. 1997. Causal theories of action and change. In Proceedings of National Conference on Artificial Intelligence (AAAI), Stanford, CA, 460–465) became the basis for the semantics of several expressive action languages. McCain's embedding of definite propositional causal theories into logic programming paved the way to the use of answer set solvers for answering queries about actions described in such languages. In this paper we extend this embedding to nondefinite theories and to the first-order causal logic.
Using Non-Additive Measure For Optimization-Based Nonlinear Classification, Nian Yan, Zhengxin Chen, Yong Shi, Zhenyuan Wang, Guimin Huang
Using Non-Additive Measure For Optimization-Based Nonlinear Classification, Nian Yan, Zhengxin Chen, Yong Shi, Zhenyuan Wang, Guimin Huang
Computer Science Faculty Publications
Over the past few decades, numerous optimization-based methods have been proposed for solving the classification problem in data mining. Classic optimization-based methods do not consider attribute interactions toward classification. Thus, a novel learning machine is needed to provide a better understanding on the nature of classification when the interaction among contributions from various attributes cannot be ignored. The interactions can be described by a non-additive measure while the Choquet integral can serve as the mathematical tool to aggregate the values of attributes and the corresponding values of a non-additive measure. As a main part of this research, a new nonlinear …
Performance And Use Evaluation Of An Electronic Book For Introductory Python Programming, Christine Alvarado, Briana B. Morrison, Barbara Ericson, Mark Guzdial, Brad Miller, David L. Ranum
Performance And Use Evaluation Of An Electronic Book For Introductory Python Programming, Christine Alvarado, Briana B. Morrison, Barbara Ericson, Mark Guzdial, Brad Miller, David L. Ranum
Computer Science Faculty Publications
Electronic books (ebooks) provide the opportunity to go beyond the limitations of a physical page. These opportunities are particularly important for computing education, where dynamic information is a key characteristic of our domain. An electronic book can provide opportunities to program or conduct analyses that are impossible on the physical page, integrating instructional information with creative exploration. However, just because ebooks provide these opportunities does not mean that we know how students will actually use ebooks in the context of a class. Miller and Ranum have produced an electronic book for teaching introductory computing in Python. We explored how students …
On Elementary Loops Of Logic Programs, Martin Gerber, Joohyung Lee, Yuliya Lierler
On Elementary Loops Of Logic Programs, Martin Gerber, Joohyung Lee, Yuliya Lierler
Computer Science Faculty Publications
Using the notion of an elementary loop, Gebser and Schaub (2005. Proceedings of the Eighth International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR'05), 53–65) refined the theorem on loop formulas attributable to Lin and Zhao (2004) by considering loop formulas of elementary loops only. In this paper, we reformulate the definition of an elementary loop, extend it to disjunctive programs, and study several properties of elementary loops, including how maximal elementary loops are related to minimal unfounded sets. The results provide useful insights into the stable model semantics in terms of elementary loops. For a nondisjunctive program, …
Centinela: A Human Activity Recognition System Based On Acceleration And Vital Sign Data, Óscar D. Lara, Alfredo J. Perez, Miguel A. Labrador, José D. Posada
Centinela: A Human Activity Recognition System Based On Acceleration And Vital Sign Data, Óscar D. Lara, Alfredo J. Perez, Miguel A. Labrador, José D. Posada
Computer Science Faculty Publications
This paper presents Centinela, a system that combines acceleration data with vital signs to achieve highly accurate activity recognition. Centinela recognizes five activities: walking, running, sitting, ascending, and descending. The system includes a portable and unobtrusive real-time data collection platform, which only requires a single sensing device and a mobile phone. To extract features, both statistical and structural detectors are applied, and two new features are proposed to discriminate among activities during periods of vital sign stabilization. After evaluating eight different classifiers and three different time window sizes, our results show that Centinela achieves up to 95.7% overall accuracy, which …
Transition Systems For Model Generators — A Unifying Approach, Yuliya Lierler, Miroslaw Truszczyński
Transition Systems For Model Generators — A Unifying Approach, Yuliya Lierler, Miroslaw Truszczyński
Computer Science Faculty Publications
A fundamental task for propositional logic is to compute models of propositional formulas. Programs developed for this task are called satisfiability solvers. We show that transition systems introduced by Nieuwenhuis, Oliveras, and Tinelli to model and analyze satisfiability solvers can be adapted for solvers developed for two other propositional formalisms: logic programming under the answerset semantics, and the logic PC(ID). We show that in each case the task of computing models can be seen as “satisfiability modulo answer-set programming,” where the goal is to find a model of a theory that also is an answer set of a certain program. …
Applications Of Hidden Markov Models In Microarray Gene Expression Data, Huimin Geng, Xutao Deng, Hesham Ali
Applications Of Hidden Markov Models In Microarray Gene Expression Data, Huimin Geng, Xutao Deng, Hesham Ali
Computer Science Faculty Publications
Hidden Markov models (HMMs) are well developed statistical models to capture hidden information from observable sequential symbols. They were first used in speech recognition in 1970s and have been successfully applied to the analysis of biological sequences since late 1980s as in finding protein secondary structure, CpG islands and families of related DNA or protein sequences [1]. In a HMM, the system being modeled is assumed to be a Markov process with unknown parameters, and the challenge is to determine the hidden parameters from the observable parameters. In this chapter, we described two applications using HMMs to predict gene functions …
An Architecture For Global Ubiquitous Sensing, Alfredo J. Perez
An Architecture For Global Ubiquitous Sensing, Alfredo J. Perez
Computer Science Faculty Publications
A new class of wireless sensor networks has recently appeared due to the pervasiness of cellular phones with embedded sensors, mobile Internet connectivity, and location technologies. This mobile wireless sensor network has the potential to address large-scale societal problems and improve the people’s quality of life in a better, faster and less expensive fashion than current solutions based on static wireless sensor networks. Ubiquitous Sensing is the umbrella term used in this dissertation that encompasses location-based services, human-centric, and participatory sensing applications. At the same time, ubiquitous sensing applications are bringing a new series of challenging problems. This dissertation proposes …
Abstract Answer Set Solvers With Backjumping And Learning, Yuliya Lierler
Abstract Answer Set Solvers With Backjumping And Learning, Yuliya Lierler
Computer Science Faculty Publications
Nieuwenhuis et al. (2006. Solving SAT and SAT modulo theories: From an abstract Davis-Putnam-Logemann-Loveland procedure to DPLL(T). Journal of the ACM 53(6), 937977 showed how to describe enhancements of the Davis–Putnam–Logemann–Loveland algorithm using transition systems, instead of pseudocode. We design a similar framework for several algorithms that generate answer sets for logic programs: SMODELS, SMODELScc, asp-sat with Learning (CMODELS), and a newly designed and implemented algorithm sup. This approach to describe answer set solvers makes it easier to prove their correctness, to compare them, and to design new systems.
A Genetic Algorithm For Multiobjective Hard Scheduling Optimization, Elías Niño, Carlos Ardila, Alfredo J. Perez, Yexid Donoso
A Genetic Algorithm For Multiobjective Hard Scheduling Optimization, Elías Niño, Carlos Ardila, Alfredo J. Perez, Yexid Donoso
Computer Science Faculty Publications
This paper proposes a genetic algorithm for multiobjective scheduling optimization based in the object oriented design with constrains on delivery times, process precedence and resource availability. Initially, the programming algorithm (PA) was designed and implemented, taking into account all constraints mentioned. This algorithm’s main objective is, given a sequence of production orders, products and processes, calculate its total programming cost and time.
Once the programming algorithm was defined, the genetic algorithm (GA) was developed for minimizing two objectives: delivery times and total programming cost. The stages defined for this algorithm were: selection, crossover and mutation. During the first stage, the …
G-Sense: A Scalable Architecture For Global Sensing And Monitoring, Alfredo J. Perez, Miguel A. Labrador, Sean J. Barbeau
G-Sense: A Scalable Architecture For Global Sensing And Monitoring, Alfredo J. Perez, Miguel A. Labrador, Sean J. Barbeau
Computer Science Faculty Publications
The pervasiveness of cellular phones combined with Internet connectivity, GPS embedded chips, location information, and integrated sensors provide an excellent platform to collect data about the individual and its surrounding environment. As a result, new applications have recently appeared to address large-scale societal problems as well as improve the quality of life of the individual. However, these new applications, recently called location-based services, participatory sensing, and human-centric sensing, bring many new challenges, one of them being the management of the huge amount of traffic (data) they generate. This article presents G-Sense, for Global-Sense, an architecture that integrates mobile and static …
A Location-Aware Framework For Intelligent Real-Time Mobile Applications, Sean J. Barbeau, Rafael A. Perez, Miguel A. Labrador, Alfredo J. Perez, Nevine Labib Georggi, Philip L. Winters
A Location-Aware Framework For Intelligent Real-Time Mobile Applications, Sean J. Barbeau, Rafael A. Perez, Miguel A. Labrador, Alfredo J. Perez, Nevine Labib Georggi, Philip L. Winters
Computer Science Faculty Publications
The Location-Aware Information Systems Client (LAISYC) supports intelligent, real-time, mobile applications for GPS-enabled mobile phones by dynamically adjusting platform parameters for application performance while conserving device resources such as battery life.
Sat-Based Answer Set Programming, Yuliya Lierler
Sat-Based Answer Set Programming, Yuliya Lierler
Computer Science Faculty Publications
Answer set programming (ASP) is a declarative programming paradigm oriented towards difficult combinatorial search problems. Syntactically, ASP programs look like Prolog programs, but solutions are represented in ASP by sets of atoms, and not by substitutions, as in Prolog. Answer set systems, such as SMODELS, SMODELSCC, and DLV, compute answer sets of a given program in the sense of the answer set (stable model) semantics. This is different from the functionality of Prolog systems, which determine when a given query is true relative to a given logic program. ASP has been applied to many areas of science and technology, from …
A Coherent Measurement Of Web-Search Relevance, William Mahoney, Peter Hospodka, William Sousan, Ryan Nickell, Qiuming Zhu
A Coherent Measurement Of Web-Search Relevance, William Mahoney, Peter Hospodka, William Sousan, Ryan Nickell, Qiuming Zhu
Computer Science Faculty Publications
We present a metric for quantitatively assessing the quality of Web searches. The relevance-of-searching-on-target index measures how relevant a search result is with respect to the searcher's interest and intention. The measurement is established on the basis of the cognitive characteristics of common user's online Web-browsing behavior and processes. We evaluated the accuracy of the index function with respect to a set of surveys conducted on several groups of our college students. While the index is primarily intended to be used to compare the Web-search results and tell which is more relevant, it can be extended to other applications. For …
Collecting Open Source Intelligence Via Tailored Information Delivery Systems, William Sousan, Qiuming Zhu, Ryan Nickell, William Mahoney, Peter Hospodka
Collecting Open Source Intelligence Via Tailored Information Delivery Systems, William Sousan, Qiuming Zhu, Ryan Nickell, William Mahoney, Peter Hospodka
Computer Science Faculty Publications
The Internet offers a plethora of freely available information for possible use in Open Source Intelligence (OSINT) operations. However, along with this information come challenges in finding relevant information and overcoming information overload. This paper presents the results of an ongoing research in a Tailored Information Delivery Services (TIDS) system that aids users in retrieving relevant information through various open intelligence sources. The TIDS provides a semantics-based query constructor that operates in a “What You Get is What You Need (WYGIWYNTM)” fashion and builds ontology based information tagging, theme extractor, and contextual model.
Incremental Procedures For Partitioning Highly Intermixed Multi-Class Datasets Into Hyper-Spherical And Hyper-Ellipsoidal Clusters, Qinglu Kong, Qiuming Zhu
Incremental Procedures For Partitioning Highly Intermixed Multi-Class Datasets Into Hyper-Spherical And Hyper-Ellipsoidal Clusters, Qinglu Kong, Qiuming Zhu
Computer Science Faculty Publications
Two procedures for partitioning large collections of highly intermixed datasets of different classes into a number of hyper-spherical or hyper-ellipsoidal clusters are presented. The incremental procedures are to generate a minimum numbers of hyper-spherical or hyper-ellipsoidal clusters with each cluster containing a maximum number of data points of the same class. The procedures extend the move-to-front algorithms originally designed for construction of minimum sized enclosing balls or ellipsoids for dataset of a single class. The resulting clusters of the dataset can be used for data modeling, outlier detection, discrimination analysis, and knowledge discovery.
A Trend Pattern Assessment Approach To Microarray Gene Expression Profiling Data Analysis, Kahai Cao, Qiuming Zhu, Javeed Iqbal, John W.C. Chan
A Trend Pattern Assessment Approach To Microarray Gene Expression Profiling Data Analysis, Kahai Cao, Qiuming Zhu, Javeed Iqbal, John W.C. Chan
Computer Science Faculty Publications
We study the problem of how to assess the reliability of a statistical measurement on data set containing unknown quantity of noises, inconsistencies, and outliers. A practical approach that analyzes the dynamical patterns (trends) of the statistical measurements through a sequential extreme-boundary-points (EBP) weed-out process is explored. We categorize the weed-out trend patterns (WOTP) and examine their relation to the reliability of the measurement. The approach is applied to the processes of extracting genes that are predictive to BCL2 translocations and to clinical survival outcomes of diffuse large B-cell lymphoma (DLBCL) from DNA Microarray gene expression profiling data sets. Fisher’s …
A Three-Tier Knowledge Management Scheme For Software Engineering Support And Innovation, Richard Corbin, Christopher B. Dunbar, Qiuming Zhu
A Three-Tier Knowledge Management Scheme For Software Engineering Support And Innovation, Richard Corbin, Christopher B. Dunbar, Qiuming Zhu
Computer Science Faculty Publications
To ensure smooth and successful transition of software innovations to enterprise systems, it is critical to maintain proper levels of knowledge about the system configuration, the operational environment, and the technology in both existing and new systems. We present a three-tier knowledge management scheme through a systematic planning of actions spanning the transition processes in levels from conceptual exploration to prototype development, experimentation, and product evaluation. The three-tier scheme is an integrated effort for bridging the development and operation communities, maintaining stability to the operational performance, and adapting swiftly to software technology innovations. The scheme combines experiences of academic researches …
Hierarchical Collective Agent Network (Hcan) For Efficient 3 Fusion And Management Of Multiple Networked Sensors, Qiuming Zhu, Stuart L. Aldridge, Tomas N. Resha
Hierarchical Collective Agent Network (Hcan) For Efficient 3 Fusion And Management Of Multiple Networked Sensors, Qiuming Zhu, Stuart L. Aldridge, Tomas N. Resha
Computer Science Faculty Publications
Agent-based software systems and applications are constructed by integrating diverse sets of components that are intelligent, heterogeneous, distributed, and concurrent. This paper describes a multi-agent system to assure the operation efficiency and reliability in data fusion and management of a set of networked distributive sensors (NDS). We discuss the general concept and architecture of a Hierarchical Collective Agent Network (HCAN) and its functional components for learning and adaptive control of the NDS. Sophistication of a HCAN control environment and an anatomy of the agent modules for enabling intelligent data fusion and management are presented. An exemplar HCAN is configured to …