Integrating Semantic Web and Software Agents

2011 ◽  
Vol 2 (1) ◽  
pp. 60-76 ◽  
Author(s):  
Yiwei Gong ◽  
Sietse Overbeek ◽  
Marijn Janssen
Keyword(s):  
Semantic Web ◽  
Intelligent Agents ◽  
Software Agents ◽  
Architectural Style ◽  
Bdi Agents ◽  
Agent Programming ◽  
Bdi Agent ◽  
Integration Architecture ◽  
Two Systems ◽  
Interchange Format

Software agents and rules are both used for creating flexibility. Exchanging rules between Semantic Web and agents can ensure consistency in rules and support easy updating and changing of rules. The Rule Interchange Format (RIF) is a new W3C recommendation Semantic Web standard for exchanging rules among disparate systems. Yet, the contribution of RIF in rules exchange between Semantic Web and software agents is unclear. The BDI architectural style is regarded as the predominant approach for the implementation of intelligent agents. This paper proposes a development for integrating RIF and BDI agents to enhance agent reasoning capabilities. This approach consists of an integration architecture and equivalence principles for rule translation. The equivalence principles are demonstrated using examples. The results show that the approach allows the integration of RIF with BDI agent programming and realize the translation between the two systems.

Integrating Semantic Web and Software Agents

2012 ◽  
pp. 82-99
Author(s):  
Yiwei Gong ◽  
Sietse Overbeek ◽  
Marijn Janssen
Keyword(s):  
Semantic Web ◽  
Intelligent Agents ◽  
Software Agents ◽  
Architectural Style ◽  
Bdi Agents ◽  
Agent Programming ◽  
Bdi Agent ◽  
Integration Architecture ◽  
Two Systems ◽  
Interchange Format

Software agents and rules are both used for creating flexibility. Exchanging rules between Semantic Web and agents can ensure consistency in rules and support easy updating and changing of rules. The Rule Interchange Format (RIF) is a new W3C recommendation Semantic Web standard for exchanging rules among disparate systems. Yet, the contribution of RIF in rules exchange between Semantic Web and software agents is unclear. The BDI architectural style is regarded as the predominant approach for the implementation of intelligent agents. This paper proposes a development for integrating RIF and BDI agents to enhance agent reasoning capabilities. This approach consists of an integration architecture and equivalence principles for rule translation. The equivalence principles are demonstrated using examples. The results show that the approach allows the integration of RIF with BDI agent programming and realize the translation between the two systems.

Integrating Semantic Web and Software Agents

2013 ◽  
pp. 102-119
Author(s):  
Yiwei Gong ◽  
Sietse Overbeek ◽  
Marijn Janssen
Keyword(s):  
Semantic Web ◽  
Intelligent Agents ◽  
Software Agents ◽  
Architectural Style ◽  
Bdi Agents ◽  
Agent Programming ◽  
Bdi Agent ◽  
Integration Architecture ◽  
Two Systems ◽  
Interchange Format

Software agents and rules are both used for creating flexibility. Exchanging rules between Semantic Web and agents can ensure consistency in rules and support easy updating and changing of rules. The Rule Interchange Format (RIF) is a new W3C recommendation Semantic Web standard for exchanging rules among disparate systems. Yet, the contribution of RIF in rules exchange between Semantic Web and software agents is unclear. The BDI architectural style is regarded as the predominant approach for the implementation of intelligent agents. This paper proposes a development for integrating RIF and BDI agents to enhance agent reasoning capabilities. This approach consists of an integration architecture and equivalence principles for rule translation. The equivalence principles are demonstrated using examples. The results show that the approach allows the integration of RIF with BDI agent programming and realize the translation between the two systems.

Intelligent Semantics Approaches for Adaptive Web

2018 ◽  
pp. 201-220
Author(s):  
Anu Sharma ◽  
Aarti Singh
Keyword(s):  
Semantic Web ◽  
Intelligent Agents ◽  
Software Agents ◽  
User Profile ◽  
Content Management ◽  
Web Personalization ◽  
New Era ◽  
Work Done ◽  
The Web

Intelligent semantic approaches (i.e., semantic web and software agents) are very useful technologies for adding meaning to the web. Adaptive web is a new era of web targeting to provide customized and personalized view of contents and services to its users. Integration of these two technologies can further add to reasoning and intelligence in recommendation process. This chapter explores the existing work done in the area of applying intelligent approaches to web personalization and highlighting ample scope for application of intelligent agents in this domain for solving many existing issues like personalized content management, user profile learning, modelling, and adaptive interactions with users.

Semantics and Agents Oriented Web Personalization

2016 ◽  
pp. 1018-1032
Author(s):  
Aarti Singh ◽  
Anu Sharma ◽  
Nilanjan Dey
Keyword(s):  
Semantic Web ◽  
Intelligent Agents ◽  
Web Mining ◽  
Information Overload ◽  
Software Agents ◽  
User Profile ◽  
Content Management ◽  
Multi Agent Systems ◽  
Web Personalization ◽  
Intelligent Software Agents

Advent of technologies like semantic web, multi-agent systems, web mining has changed the internet as knowledge provider. Web personalization offers a solution to the information overload problem in current web by providing users a personalized experience, considering their interest, behavior, context and emotions. Semantic web technology is based on use of software agents, ontologies and reasoning to add meaning to web information. An important technology for achieving personalization is the use of independent intelligent software agents. This work reviews, web personalization in the light of semantic web and software agent technology. A comparative study of recent works in the domain of web personalization has been carried out for this purpose. This review highlights ample scope for application of intelligent agents in the web personalization domain for solving many existing issues like personalized content management, user profile learning, modeling and adaptive interactions with users.

Semantics and Agents Oriented Web Personalization

2015 ◽  
Vol 6 (2) ◽  
pp. 35-49 ◽  
Author(s):  
Aarti Singh ◽  
Anu Sharma ◽  
Nilanjan Dey
Keyword(s):  
Semantic Web ◽  
Intelligent Agents ◽  
Web Mining ◽  
Information Overload ◽  
Software Agents ◽  
User Profile ◽  
Content Management ◽  
Multi Agent Systems ◽  
Web Personalization ◽  
Intelligent Software

Advent of technologies like semantic web, multi-agent systems, web mining has changed the internet as knowledge provider. Web personalization offers a solution to the information overload problem in current web by providing users a personalized experience, considering their interest, behavior, context and emotions. Semantic web technology is based on use of software agents, ontologies and reasoning to add meaning to web information. An important technology for achieving personalization is the use of independent intelligent software agents. This work reviews, web personalization in the light of semantic web and software agent technology. A comparative study of recent works in the domain of web personalization has been carried out for this purpose. This review highlights ample scope for application of intelligent agents in the web personalization domain for solving many existing issues like personalized content management, user profile learning, modeling and adaptive interactions with users.

Reinforcement Learning-Based Intelligent Agents for Improved Productivity in Container Vessel Berthing Applications

2011 ◽  
pp. 155-184 ◽  
Author(s):  
Prasanna Lokuge ◽  
Damminda Alahakoon
Keyword(s):  
Reinforcement Learning ◽  
Intelligent Agents ◽  
Fuzzy Inference ◽  
Container Terminals ◽  
Bdi Agents ◽  
Inference System ◽  
Business Applications ◽  
Neuro Fuzzy ◽  
Bdi Agent ◽  
Intelligent Behavior

This chapter introduces the use of hybrid intelligent agents in a vessel berthing application. Vessel berthing in container terminals is regarded as a very complex, dynamic application, which requires autonomous decision-making capabilities to improve the productivity of the berths. In this chapter, the dynamic nature of the container vessel berthing system has been simulated with reinforcement learning theory, which essentially learns what to do by interaction with the environment. Other techniques, such as Belief-Desire-Intention (BDI) agent systems have also been implemented in many business applications. The chapter proposes a new hybrid agent model using an Adaptive Neuro Fuzzy Inference System (ANFIS), neural networks, and reinforcement learning methods to improve the reactive, proactive and intelligent behavior of generic BDI agents in a shipping application.

scholarly journals BDI Agent Architectures: A Survey

2020 ◽  
Author(s):  
Lavindra de Silva ◽  
Felipe Meneguzzi ◽  
Brian Logan
Keyword(s):  
Systematic Review ◽  
Software Engineering ◽  
Programming Languages ◽  
Agent Architectures ◽  
Agent Oriented Software Engineering ◽  
Agent Programming ◽  
Agent Programming Languages ◽  
Trade Offs ◽  
Bdi Agent ◽  
Bdi Architecture

The BDI model forms the basis of much of the research on symbolic models of agency and agent-oriented software engineering. While many variants of the basic BDI model have been proposed in the literature, there has been no systematic review of research on BDI agent architectures in over 10 years. In this paper, we survey the main approaches to each component of the BDI architecture, how these have been realised in agent programming languages, and discuss the trade-offs inherent in each approach.

Intelligent Agents and Autonomous Robots

2019 ◽  
pp. 1134-1143
Author(s):  
Deepshikha Bhargava
Keyword(s):  
Language Processing ◽  
Intelligent Agents ◽  
Driving Force ◽  
Autonomous Agents ◽  
New Technologies ◽  
Autonomous Robots ◽  
Software Agents ◽  
Intelligent Agent ◽  
Intelligent Robots ◽  
Systems Software

Over decades new technologies, algorithms and methods are evolved and proposed. We can witness a paradigm shift from typewriters to computers, mechanics to mechnotronics, physics to aerodynamics, chemistry to computational chemistry and so on. Such advancements are the result of continuing research; which is still a driving force of researchers. In the same way, the research in the field of artificial intelligence (Russell, Stuart & Norvig, 2003) is major thrust area of researchers. Research in AI have coined different concepts like natural language processing, expert systems, software agents, learning, knowledge management, robotics to name a few. The objective of this chapter is to highlight the research path from software agents to robotics. This chapter begins with the introduction of software agents. The chapter further progresses with the discussion on intelligent agent, autonomous agents, autonomous robots, intelligent robots in different sections. The chapter finally concluded with the fine line between intelligent agents and autonomous robots.

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