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Titlebook: Agent-Oriented Information Systems II; 6th International Bi Paolo Bresciani,Paolo Giorgini,Michael Winikoff Conference proceedings 2005 Spr

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樓主: corrode
11#
發(fā)表于 2025-3-23 12:38:31 | 只看該作者
12#
發(fā)表于 2025-3-23 15:49:30 | 只看該作者
Analyzing Multiparty Agreements with Commitmentsent based on their individual constraints. The actual execution sequence is validated by checking the compliance of commitment casual relations. Our approach is geared toward constructing business processes where agents are mutually constrained in a manner that preserves their autonomy and heterogeneity.
13#
發(fā)表于 2025-3-23 18:25:02 | 只看該作者
AgentZ: Extending Object-Z for Multi-agent Systems Specificationuilt to provide a formal notation that allows the verification of design models, a key issue within the emerging agent-oriented software engineering research and, as a result, it can help to improve the quality of MAS.
14#
發(fā)表于 2025-3-24 00:47:53 | 只看該作者
15#
發(fā)表于 2025-3-24 04:32:29 | 只看該作者
A Preliminary Comparative Feature Analysis of Multi-agent Systems Development Methodologiesuation criteria, covering both agent-oriented aspects and system engineering dimensions. The analysis also compares the methodologies in terms of their support for the steps in the development process and for agent-oriented concept modeling.
16#
發(fā)表于 2025-3-24 08:57:54 | 只看該作者
17#
發(fā)表于 2025-3-24 13:39:44 | 只看該作者
A Systematic Approach for Including Machine Learning in Multi-agent Systemslearning strategies. This process supports the stepwise building of adaptable MASs for unknown situations, improving their capacity to scale up. We use the Trading Agent Competition (TAC) environment as a case study to illustrate the suitability of our approach.
18#
發(fā)表于 2025-3-24 14:55:45 | 只看該作者
19#
發(fā)表于 2025-3-24 20:12:05 | 只看該作者
20#
發(fā)表于 2025-3-25 02:09:32 | 只看該作者
Alette Vonk,Vasco Freitas Silvalearning strategies. This process supports the stepwise building of adaptable MASs for unknown situations, improving their capacity to scale up. We use the Trading Agent Competition (TAC) environment as a case study to illustrate the suitability of our approach.
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