1. 毕业设计（论文）的内容和要求

内容：本课题是以无线传感器网络为背景，研究应用多代理协调的和积算法。

无线传感器信道分配问题可以转换成图形着色问题。

图形着色问题是np-c问题，这类问题没有高效的、精确的快速求解方法，目前解决该类问题主要采用近似方法，例如集中式的遗传算法，本文采用分布式方法，即用和积算法来解决图形着色问题，从而开展各种应用。

2. 参考文献

1.志鑫, 郝燕玲. Tanner图和积算法的伪码捕获及性能分析[J]. 北京邮电大学学报, 2009, 32(3):50-54. 2.吕香玲, 张志勇, 胡光岷. 基于因子图#8212;和积算法的故障链路诊断[J]. 计算机应用, 2012, 32(02):343-346. 3.耿蕾蕾, 蔚承建. 基于混沌序列的最大和分散式协调算法[J]. 计算机工程与应用, 2010(31):57-60. 4.耿蕾蕾, 蔚承建. 改进的最大和分散式协调算法[J]. Journal of Computer Applications, 2010(8):2073-2076. 5.Ammari, H. M., Das, S. R. (2009). Fault tolerance measures for large-scale wireless sensor networks.ACM Transactions on Autonomous and Adaptive System, 4(1), 1#8211;28. 6.Farinelli, A., Rogers, A., Jennings, N. R. (2008). Maximising sensor network ef#64257;ciency through agent-based coordination of sense/sleep schedules. In Proceedings of the Workshop on Energy in Wireless Sensor Networks in conjuction with DCOSS 2008. 7.Guestrin, C., Koller, D., Parr, R. (2001). Multiagent planning with factored mdps. In Advances in neural information processing systems (NIPS), pp. 1523#8211;1530, Vancouver. 8.Guestrin, C., Lagoudakis, M., Parr, R. (2002). Coordinated reinforcement learning. In Proceedings of ICML-02, pp. 227#8211;234. 9.Kansal, A., Hsu, J., Zahedi, S., Srivastava, M. B. (2007). Power management in energy harvesting sensor networks. ACM Transactions on Embedded Computing Systems, 6(4), 54#8211;61. 10.Kok, J. R., Vlassis, N. (December 2006). Collaborative multiagent reinforcement learning by payoff propagation. Journal of Machine Learning Research, 7, 1789#8211;1828. 11. MacKay, D. J. C. (2003). Information theory, inference, and learning algorithms. New York: Cambridge University Press. 12.Makarenko, A., Durrant-Whyte, H.F. (2004). Decentralized data fusion and control algorithms in active sensor networks. In Proceedings of Seventh International Conference on Information Fusion (Fusion 2004), pp. 479#8211;486. 13.Modi, P. J., Scerri, P., Shen, W. M., Tambe, M. (2003). Distributed sensor networks a multiagent perspective, chapter distributed resource allocation (pp. 219#8211;256). Dordrecht: Kluwer Academic. 14.Ramchurn, S., Farinelli, A., Macarthur, K., Polukarov, M., Jennings, N. R. (2010). Decentralised coordination in robocup rescue. The Computer Journal, 53(9), 1#8211;15. 15.Rogers,A.,David,E.,Jennings,N.R.(2005).Self-organizedroutingforwirelessmicrosensornetwors. Systems Man and Cybernetics Part A IEEE Transactions, 35(3), 349#8211;359. 16.Stefanovitch, N., Farinelli, A., Rogers, A., Jennings, N. R. (2011). Resource-aware junction trees for ef#64257;-cient multi-agent coordination. In Tenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), pp. 363#8211;370, Taipei. 17.Stranders, R., Farinelli, A., Rogers, A., Jennings, N. R. (2009). Decentralised coordination of mobile sensors using the max-sum algorithm. In Proceedings of the Twenty-First International Joint Conference on Arti#64257;cial Intelligence, pp. 299#8211;304. 18.Teacy W. T. L., Farinelli, A., Grabham, N. J., Padhy, P., Rogers, A., Jennings, N. R. (2008). Max-sum decentralised coordination for sensor systems. In 7th International Conference on Autonomous Agents and Multiagent Systems, pp. 1697#8211;1698. 19.Vinyals, M., Rodriguez-Aguilar, J., Cerquides, J. (2011). Constructing a unifying theory of dynamic programming dcop algorithms via the generalized distributive law. Autonomous Agents and Multi-Agent Systems, 22, 439#8211;464. 20.Zhang, W., Wang, G., Xing, Z., Wittenburg, L. (January 2005). Distributed stochastic search and distributed breakout: Properties, comparison and applications to constraint optimization problems in sensor networks. Arti#64257;cial Intelligence, 161(1#8211;2), 55#8211;87.

3. 毕业设计（论文）进程安排

20180116-20180303 撰写开题报告 20180304-20180415 程序原型设计 20180416-20180430 各模块完善 20180501-20180515 系统测试 20180516-20180530 撰写论文 20180601 交论文初稿 20180605-20180612 修改论文 20180615 答辩