By Béatrice Duval, Jaap van den Herik, Stephane Loiseau, Joaquim Filipe
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Extra resources for Agents and Artificial Intelligence: 7th International Conference, ICAART 2015, Lisbon, Portugal, January 10-12, 2015, Revised Selected Papers (Lecture Notes in Computer Science)
After the generation of the dynamic sub-problem, we can launch the resolution following the same approach as before, but instead to insert the name of an XML ﬁle of a static sub-problem as argument, we insert the name of dynamic sub-problem XML. 93 GHz, CORE(TM) 2 duo with 2 GB RAM that simulate agents. These machines are connected via the WLAN of our laboratory. We also chose ABT algorithm to solve Meeting Scheduling problems (MSP). In Fig. 1 above, we depict an example of problem solved by this platform in a live distributed environment network.
Section 2 outlines our approach. Section 3 provides an overview of the SXM formal modelling technique, how SXM concepts are mapped to agent concepts and an introduction to SXM testing. The TXStates DSL is presented in Sect. 4. Section 5 describes the model used as a working example in the current paper. The process of moving from speciﬁcation to testing using the JSXM tool is described in Sect. 6. Related work is presented in Sect. 7. Finally, Sect. 8 concludes the work and presents future work.
In: AAMAS08: Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 591–598 (2008) 15. : Dynamic backtracking for distributed constraint optimization. Proceeding of the 2008 conference on ECAI 2008, pp. 901–902. The Netherlands, IOS Press, Amsterdam (2008) 16. : Algorithms for distributed constraint satisfaction problems: a review. Auton. Agents Multiagent Syst. 3, 185–207 (2000) 17. : The distributed constraint satisfaction problem: formalization and algorithms.