Swarm intelligence: tools and applications

该提案的目标是开发理论，工具和技术，以促进使用群智能解决问题的系统的构建。为了实现在基于群的系统中的信息处理的理解，我们建议开发一个新的信息场视图。我们希望，这是基于研究者自己的博士学位。论文，Bandini等人的Situated Cellular Agents的工作以及我们自己在理解基于交互信息场的群体动力学方面的工作的扩展。作为实际的例子，建议的理论制定的效用，我们希望应用群算法的问题，在该地区的机器人足球，并继续在人群的理解工作。我们在前一个问题的重点将是动态的角色分配，而在后一个问题的理解如何信息可以更有效地在人群中进行沟通，以影响，例如，从建筑物更rapidegress。我们希望使用进化算法，如遗传编程，以便以类似于SwarmBot项目的方式为基于群的机器人开发代理行为，该项目使用神经网络进行机器人行为。在理解传感器网络的过程中，我们希望开发出一种算法，确保在单个传感器发生故障的情况下收集强大的信息;同样，进化计算的技术有望提供行为。作为群处理效用的进一步证明，我们期望解决自治计算领域的问题。在这里，我们预计自主管理者-代理的另一个名字-将学会自我组织自动化管理下一代计算机系统。

The objectives of the proposal are to develop theories, tools and techniques that facilitate the construction ofsystems which solve problems using Swarm Intelligence. In order to achieve an understanding of information processing in swarm-based systems, we propose that a new information field view be developed. This, we expect, to be based upon the investigator's own Ph.D. thesis, the work of Situated Cellular Agents of Bandini et al and extensions of our own work in understanding crowd dynamics based upon interacting information fields. As practical examples of the utility of the proposed theoretical formulation, we expect to apply swarm algorithms to problems in the area of robotic soccer and continue work in the understanding of crowds. Our focus in the former problem will be dynamic role assignment, while in the latter problem understanding how  information can be more effectively communicated within a crowd in order to effect, for example, more rapidegress from a building. We expect to use evolutionary algorithms, such as Genetic Programming, in order todevelop agent behaviours for swarm-based robots in a manner similar to the SwarmBot project, which usesneural networks for robot behavior. In understanding sensor networks we expect to develop algorithms thatensure robust information gathering in scenarios where individual sensors fail; again, techniques fromEvolutionary Computation are expected to be provide behaviours. As a further demonstration of the utility ofswarm processing, we expect to solve problems in the area of Autonomic Computing. Here, we anticipate thatautonomic managers -- agents by another name -- will learn to self organize to automate the management ofnext-generation computer systems.