scholarly journals Driftage: a multi-agent system framework for concept drift detection

GigaScience ◽  
2021 ◽  
Vol 10 (6) ◽  
Author(s):  
Diogo Munaro Vieira ◽  
Chrystinne Fernandes ◽  
Carlos Lucena ◽  
Sérgio Lifschitz
Keyword(s):  
Concept Drift ◽  
Knowledge Bases ◽  
Machine Learning Algorithms ◽  
Behavior Changes ◽  
Multi Agent Systems ◽  
New Paradigm ◽  
Detection Algorithms ◽  
Multi Agent ◽  
Concept Drift Detection ◽  
And Behavior

Abstract Background The amount of data and behavior changes in society happens at a swift pace in this interconnected world. Consequently, machine learning algorithms lose accuracy because they do not know these new patterns. This change in the data pattern is known as concept drift. There exist many approaches for dealing with these drifts. Usually, these methods are costly to implement because they require (i) knowledge of drift detection algorithms, (ii) software engineering strategies, and (iii) continuous maintenance concerning new drifts. Results This article proposes to create Driftage: a new framework using multi-agent systems to simplify the implementation of concept drift detectors considerably and divide concept drift detection responsibilities between agents, enhancing explainability of each part of drift detection. As a case study, we illustrate our strategy using a muscle activity monitor of electromyography. We show a reduction in the number of false-positive drifts detected, improving detection interpretability, and enabling concept drift detectors’ interactivity with other knowledge bases. Conclusion We conclude that using Driftage, arises a new paradigm to implement concept drift algorithms with multi-agent architecture that contributes to split drift detection responsability, algorithms interpretability and more dynamic algorithms adaptation.

Heuristic ensemble for unsupervised detection of multiple types of concept drift in data stream classification

2021 ◽  
pp. 1-14
Author(s):  
Hanqing Hu ◽  
Mehmed Kantardzic
Keyword(s):  
Data Stream ◽  
Concept Drift ◽  
False Alarms ◽  
Detection Accuracy ◽  
Real World Data ◽  
Traditional Concept ◽  
Stream Classification ◽  
Data Stream Classification ◽  
Detection Algorithms ◽  
Concept Drift Detection

Real-world data stream classification often deals with multiple types of concept drift, categorized by change characteristics such as speed, distribution, and severity. When labels are unavailable, traditional concept drift detection algorithms, used in stream classification frameworks, are often focused on only one type of concept drift. To overcome the limitations of traditional detection algorithms, this study proposed a Heuristic Ensemble Framework for Drift Detection (HEFDD). HEFDD aims to detect all types of concept drift by employing an ensemble of selected concept drift detection algorithms, each capable of detecting at least one type of concept drift. Experimental results show HEFDD provides significant improvement based on the z-score test when comparing detection accuracy with state-of-the-art individual algorithms. At the same time, HEFDD is able to reduce false alarms generated by individual concept drift detection algorithms.

Design Patterns for Social Intelligent Agent Architectures Implementation

2021 ◽  
pp. 294-319
Author(s):  
Manuel Kolp ◽  
Yves Wautelet ◽  
Samedi Heng
Keyword(s):  
Design Patterns ◽  
Architectural Design ◽  
Autonomous Agents ◽  
Knowledge Bases ◽  
Multi Agent Systems ◽  
Business Systems ◽  
Agent Architectures ◽  
Social Patterns ◽  
Agent Oriented Software Engineering ◽  
Multi Agent

Multi-agent systems (MAS) architectures are popular for building open, distributed, and evolving software required by today's business IT applications such as e-business systems, web services, or enterprise knowledge bases. Since the fundamental concepts of MAS are social and intentional rather than object, functional, or implementation-oriented, the design of MAS architectures can be eased by using social patterns. They are detailed agent-oriented design idioms to describe MAS architectures as composed of autonomous agents that interact and coordinate to achieve their intentions like actors in human organizations. This chapter presents social patterns and focuses on a framework aimed to gain insight into these patterns. The framework can be integrated into agent-oriented software engineering methodologies used to build MAS. The authors consider the broker social pattern to illustrate the framework. The mapping from system architectural design (through organizational architectural styles), to system detailed design (through social patterns), is overviewed with a data integration case study.

Engineering Software Systems with Social-Driven Templates

2010 ◽  
pp. 1-29
Author(s):  
Manuel Kolp ◽  
Yves Wautelet ◽  
Sodany Kiv ◽  
Vi Tran
Keyword(s):  
Architectural Design ◽  
Autonomous Agents ◽  
Knowledge Bases ◽  
Software Systems ◽  
Multi Agent Systems ◽  
Business Systems ◽  
Agent Systems ◽  
Social Patterns ◽  
Engineering Software ◽  
Multi Agent

Multi-Agent Systems (MAS) architectures are gaining popularity over traditional ones for building open, distributed, and evolving software required by today’s corporate IT applications such as e-business systems, Web services or enterprise knowledge bases. Since the fundamental concepts of multi-agent systems are social and intentional rather than object, functional, or implementation-oriented, the design of MAS architectures can be eased by using social-driven templates. They are detailed agent-oriented design idioms to describe MAS architectures as composed of autonomous agents that interact and coordinate to achieve their intentions, like actors in human organizations. This paper presents social patterns, as well as organizational styles, and focuses on a framework aimed to gain insight into these templates. The framework can be integrated into agent-oriented software engineering methodologies used to build MAS. We consider the Broker social pattern to illustrate the framework. The mapping from system architectural design (through organizational architectural styles), to system detailed design (through social patterns), is overviewed with a data integration case study. The automation of patterns design is also overviewed.

Social Structure Based Design Patterns for Agent-Oriented Software Engineering

2009 ◽  
pp. 773-796
Author(s):  
Manuel Kolp ◽  
Stéphane Faulkner ◽  
Yves Wautelet
Keyword(s):  
Software Engineering ◽  
Design Patterns ◽  
Autonomous Agents ◽  
Knowledge Bases ◽  
Multi Agent Systems ◽  
Business Systems ◽  
Agent Systems ◽  
Social Patterns ◽  
Agent Oriented Software Engineering ◽  
Multi Agent

Multi-agent systems (MAS) architectures are gaining popularity over traditional ones for building open, distributed, and evolving software required by today’s corporate IT applications such as e-business systems, Web services, or enterprise knowledge bases. Since the fundamental concepts of multi-agent systems are social and intentional rather than object, functional, or implementationoriented, the design of MAS architectures can be eased by using social patterns. They are detailed agent-oriented design idioms to describe MAS architectures composed of autonomous agents that interact and coordinate to achieve their intentions, like actors in human organizations. This article presents social patterns and focuses on a framework aimed to gain insight into these patterns. The framework can be integrated into agent-oriented software engineering methodologies used to build MAS. We consider the Broker social pattern to illustrate the framework. An overview of the mapping from system architectural design (through organizational architectural styles), to system detailed design (through social patterns), is presented with a data integration case study. The automation of creating design patterns is also discussed.

A METHODOLOGY FOR MODELING MULTI-AGENT SYSTEMS USING NESTED PETRI NETS

2012 ◽  
Vol 22 (07) ◽  
pp. 891-925 ◽  
Author(s):  
LILY CHANG ◽  
XUDONG HE ◽  
SOL M. SHATZ
Keyword(s):  
Formal Model ◽  
Dynamic Structure ◽  
Software Systems ◽  
Multi Agent Systems ◽  
New Paradigm ◽  
Distributed Software ◽  
Agent Systems ◽  
Multi Agent ◽  
Communication And Coordination ◽  
Multi Agents

In the past two decades, multi-agent systems have emerged as a new paradigm for conceptualizing large and complex distributed software systems. Even though there are many conceptual frameworks for using multi-agent systems, there is no well established and widely accepted method for the representation of multi-agent systems. We adapt a well-known formal model, predicate transition nets, to include the notions of dynamic structure, agent communication and coordination to address the representation problems. This paper presents a comprehensive methodology for modeling multi-agents based on the extensions. We demonstrate our modeling approach with an example. Several case studies on different application domains from our previous works are also discussed.

scholarly journals Data stream mining: methods and challenges for handling concept drift

2019 ◽  
Vol 1 (11) ◽  
Author(s):  
Scott Wares ◽  
John Isaacs ◽  
Eyad Elyan
Keyword(s):  
Data Stream ◽  
Concept Drift ◽  
Relevant Literature ◽  
Streaming Data ◽  
Future Research ◽  
Stream Mining ◽  
Detection Algorithms ◽  
The Past ◽  
Concept Drift Detection ◽  
The Impact

Abstract Mining and analysing streaming data is crucial for many applications, and this area of research has gained extensive attention over the past decade. However, there are several inherent problems that continue to challenge the hardware and the state-of-the art algorithmic solutions. Examples of such problems include the unbound size, varying speed and unknown data characteristics of arriving instances from a data stream. The aim of this research is to portray key challenges faced by algorithmic solutions for stream mining, particularly focusing on the prevalent issue of concept drift. A comprehensive discussion of concept drift and its inherent data challenges in the context of stream mining is presented, as is a critical, in-depth review of relevant literature. Current issues with the evaluative procedure for concept drift detectors is also explored, highlighting problems such as a lack of established base datasets and the impact of temporal dependence on concept drift detection. By exposing gaps in the current literature, this study suggests recommendations for future research which should aid in the progression of stream mining and concept drift detection algorithms.

Design Patterns for Social Intelligent Agent Architectures Implementation

2018 ◽  
pp. 258-283 ◽  
Author(s):  
Manuel Kolp ◽  
Yves Wautelet ◽  
Samedi Heng
Keyword(s):  
Design Patterns ◽  
Architectural Design ◽  
Autonomous Agents ◽  
Knowledge Bases ◽  
Multi Agent Systems ◽  
Business Systems ◽  
Agent Architectures ◽  
Social Patterns ◽  
Agent Oriented Software Engineering ◽  
Multi Agent

Multi-agent systems (MAS) architectures are popular for building open, distributed, and evolving software required by today's business IT applications such as e-business systems, web services, or enterprise knowledge bases. Since the fundamental concepts of MAS are social and intentional rather than object, functional, or implementation-oriented, the design of MAS architectures can be eased by using social patterns. They are detailed agent-oriented design idioms to describe MAS architectures as composed of autonomous agents that interact and coordinate to achieve their intentions like actors in human organizations. This chapter presents social patterns and focuses on a framework aimed to gain insight into these patterns. The framework can be integrated into agent-oriented software engineering methodologies used to build MAS. The authors consider the broker social pattern to illustrate the framework. The mapping from system architectural design (through organizational architectural styles), to system detailed design (through social patterns), is overviewed with a data integration case study.

scholarly journals Introduction to the special issue on ontologies in agent systems

2002 ◽  
Vol 17 (1) ◽  
pp. 1-5 ◽  
Author(s):  
STEPHEN CRANEFIELD ◽  
STEVEN WILLMOTT ◽  
TIM FININ
Keyword(s):  
Speech Acts ◽  
Coupled System ◽  
Knowledge Bases ◽  
Message Content ◽  
Multi Agent Systems ◽  
Distributed Information ◽  
Agent Systems ◽  
Loosely Coupled ◽  
Systems Research ◽  
Multi Agent

It is now more than ten years since researchers in the US Knowledge Sharing Effort envisaged a future where complex systems could be built by combining knowledge and services from multiple knowledge bases and the first agent communication language, KQML, was proposed (Neches et al., 1991). This model of communication, based on speech acts, a declarative message content representation language and the use of explicit ontologies defining the domains of discourse (Genesereth & Ketchpel, 1994), has become widely recognised as having great benefits for the integration of disparate and distributed information sources to form an open, extensible and loosely coupled system. In particular, this idea has become a key tenet in the multi-agent systems research community.

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