Constraint-based computational intelligence

基于约束的计算智能

• 批准号: 9281-2006
• 负责人: Mackworth, Alan
• 金额: $ 4.37万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2008
• 资助国家: 加拿大
• 起止时间: 2008-01-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=389951
• 关键词: Constraint; based; computational; intelligence

This research program is focused on constraint-based computational intelligence. We have developed a formal theory for the design and implementation of constraint-based intelligent systems. Our Constraint-Based agent (CBA) framework is a set of theoretical and practical tools for designing, simulating, building, verifying, optimizing, learning and debugging controllers for agents embedded in an active environment. The agent and the environment are modelled symmetrically as, possibly hybrid, systems in the Constraint Net (CN) dynamical systems language, as developed in this research program. We intend to develop and apply the CBA framework, emphasizing the important special case where the agent is an online constraint-satisfying device. Here it is often possible to verify complex agents as obeying real-time temporal constraint specifications and, sometimes, to synthesize controllers automatically. The CBA framework demonstrates the power of viewing constraint programming as the creation of online constraint-solvers for dynamic constraints.Our objectives over the next five years are to develop the theory further and to validate and improve it using experimental implementations on varous robotic systems in our lab. This research program is focused on constraint-based computational intelligence. We have developed a formal theory for the design and implementation of constraint-based intelligent systems.The experimental environment for this work includes the soccer-playing platforms pioneered by us, a CBA Java environment and a set of mobile robots with on-board real-time stereo and colour vision. We propose to use CBA models for the control, perception and coordination algorithms required for multi-agent real-time collaborative activities such as soccer, navigation and manipulation. The scientific novelty of this approach stems from its formal foundation, its practicality and its simplicity as a unitary theory of hybrid intelligent systems. The symmetry of the agent-environment pair model is necessary and unique. The technical significance is that it is a foundation for a new design framework for perceptual, collaborative, constraint-based agents.

该研究计划的重点是基于约束的计算智能。我们已经开发了一个正式的理论设计和实现的约束为基础的智能系统。我们的基于约束的代理（CBA）框架是一套理论和实用的工具，用于设计，模拟，构建，验证，优化，学习和调试控制器嵌入在一个活跃的环境中的代理。代理和环境的对称建模，可能是混合动力系统的约束网络（CN）的动态系统语言，在本研究计划中开发的。我们打算开发和应用CBA框架，强调重要的特殊情况下，代理是一个在线约束满足设备。在这里，它往往是可以验证复杂的代理遵守实时时间约束规范，有时，自动合成控制器。CBA框架展示了将约束编程视为动态约束的在线约束求解器的能力，我们在未来五年的目标是进一步发展该理论，并在我们实验室的各种机器人系统上使用实验实现来验证和改进它。该研究计划的重点是基于约束的计算智能。我们已经开发了一个正式的理论为设计和实施的约束为基础的智能systems.The实验环境，这项工作包括足球比赛平台，我们开创了CBA Java环境和一组移动的机器人与板上实时立体和彩色视觉。我们建议使用CBA模型的控制，感知和协调算法所需的多智能体实时协作活动，如足球，导航和操纵。这种方法的科学新奇源于它的形式基础，它的实用性和它的简单性作为一个单一的混合智能系统理论。主体-环境对模型的对称性是必要的和唯一的。其技术意义在于，它是一个新的设计框架的感知，协作，基于约束的代理人的基础。