By Zili Zhang, Chengqi Zhang
Solving complicated difficulties in real-world contexts, corresponding to monetary funding making plans or mining huge facts collections, includes many various sub-tasks, each one of which calls for assorted ideas. to accommodate such difficulties, a good range of clever ideas can be found, together with conventional concepts like professional structures methods and delicate computing ideas like fuzzy good judgment, neural networks, or genetic algorithms. those options are complementary methods to clever info processing instead of competing ones, and hence greater ends up in challenge fixing are accomplished while those concepts are mixed in hybrid clever structures. Multi-Agent platforms are splendid to version the manifold interactions one of many various parts of hybrid clever systems.
This e-book introduces agent-based hybrid clever structures and offers a framework and method taking into account the advance of such structures for real-world purposes. The authors specialise in purposes in monetary funding making plans and knowledge mining.
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Additional resources for Agent-Based Hybrid Intelligent Systems: An Agent-Based Framework for Complex Problem Solving
3 Basics of Agents and Multi-agent Systems Agents (adaptive or intelligent agents and multi-agent systems) constitute one of the most prominent and attractive technologies in Computer Science at the beginning of this new century. Agent and multi-agent system technologies, methods, and theories are currently contributing to many diverse domains. These include information retrieval, user interface design, robotics, electronic commerce, computer mediated collaboration, computer games, education and training, smart environments, ubiquitous computers, and social simulation.
2 Agents as a Paradigm for Software Engineering When building hybrid intelligent systems from agent perspectives, each intelligent technique is a construction module in the form of an agent. That is, agents are building blocks in agent-based hybrid intelligent systems. This is one of the views of agents – agents as a paradigm for software engineering . Software engineers have derived a progressively better understanding of the characteristics of complexity in software. It is now widely recognized that interaction is probably the most important single characteristic of complex software.
5 Methodology for Analysis and Design of Agent-Based Hybrids 47 In Gaia methodology, analysis and design are well-separated phases. The analysis phase aims to identify what the actual organization of the multiple agents should look like. , the roles to be played in the organization, and the way in which they interact accordingly to speciﬁc protocols. This deﬁnes the role model and interaction model . The design phase starts from the models deﬁned during the analysis phase and aims to deﬁne the actual agent system in such a way that it can easily be implemented.
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