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: 2006
• 资助国家: 加拿大
• 起止时间: 2006-01-01 至 2007-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=338363
• 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.

本研究项目的重点是基于约束的计算智能。我们已经开发了一种设计和实现基于约束的智能系统的形式化理论。我们的基于约束的代理（CBA）框架是一套理论和实践工具，用于设计、模拟、构建、验证、优化、学习和调试嵌入在活动环境中的代理控制器。在本研究项目中开发的约束网（CN）动力系统语言中，智能体和环境被对称地建模为可能是混合的系统。我们打算开发和应用CBA框架，强调代理是在线约束满足设备的重要特殊情况。在这里，通常可以验证复杂的代理是否遵守实时时间约束规范，有时还可以自动合成控制器。CBA框架展示了将约束规划视为创建动态约束的在线约束求解器的强大功能。我们未来五年的目标是进一步发展这一理论，并在我们实验室的各种机器人系统上通过实验实现来验证和改进它。本研究项目的重点是基于约束的计算智能。我们已经开发了一种设计和实现基于约束的智能系统的形式化理论。这项工作的实验环境包括我们首创的足球游戏平台，CBA Java环境和一套具有车载实时立体视觉和彩色视觉的移动机器人。我们建议将CBA模型用于多智能体实时协作活动（如足球、导航和操作）所需的控制、感知和协调算法。这种方法的科学新颖性源于它的形式基础、实用性和作为混合智能系统的统一理论的简单性。agent-环境对模型的对称性是必要且唯一的。其技术意义在于，它为基于感知、协作和约束的智能体的新设计框架奠定了基础。