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Spatial reasoning for intelligent action and for human-robot interaction

机译:智能行动和人机交互的空间推理

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Successful and robust communication between cognitive agents, inparticular between humans and robots, requires shared concepts betweenthe communicating agents. In my lecture, I will present spatial robotenvironments as an example for domains of interaction between cogni-tive agents in which spatial information to be communicated needs to bephysically grounded in the environment. I will give examples of spatialcommunication tasks and discuss levels of abstraction for spatial infor-mation and knowledge from the physical level. I will show how spatialcontext can be exploited for cognitive off-loading to make communica-tion effective and efficient. With this approach, I will motivate the situ-ation-dependent selection of appropriate levels of conceptualization forspatial knowledge. The talk will present qualitative spatial abstraction asa suitable approach to establish a conceptual level of spatial knowledgethat supports an important class of communication and reasoning tasks. Iwill discuss how this conceptual level relates to the more commonquantitative representations of spatial robot environments for autono-mous robots. I will propose ways in which the different forms of repre-sentation may be combined for fruitful interaction. I will discussadvantages and disadvantages of various forms of representation fordifferent tasks and purposes. In the talk, I will present examples of spatialreasoning with qualitative representations and illustrate importantproperties of these representations. Navigation tasks will serve asexample for tasks in which detailed quantitative planning may beundesirable. Although in some sense, qualitative representations aremore abstract than quantitative representations, in another sense they aremore concrete, as they maintain important structural properties of spatio-temporal events that are relevant to spatial cognition. This raises the issueof 'cognitive adequacy' of spatial representations, which I will alsoaddress in my talk. It also raises the issue of the respective expressivepower of qualitative versus quantitative analysis. Finally, my talk willaddress the relation between spatial and linguistic forms of representingspatial knowledge, for example, maps and textual descriptions of space:they can be viewed as alternative or complementary ways of communi-cating knowledge, each having their specific advantages.
机译:认知主体之间(尤其是人与机器人之间)的成功而强大的沟通,需要沟通主体之间具有共享的概念。在我的演讲中,我将以空间机器人环境为例,说明认知主体之间相互作用的领域,在该领域中,要交流的空间信息需要在环境上进行物理化处理。我将举例说明空间通信任务,并从物理层面讨论空间信息和知识的抽象层次。我将展示如何利用空间上下文来减轻认知负担,从而使通信更加有效。通过这种方法,我将激发针对具体情况的对空间知识概念层次的依赖于情境的选择。演讲将提出定性空间抽象,作为一种建立空间知识概念水平的合适方法,该知识水平支持一类重要的交流和推理任务。我将讨论这个概念层次如何与自治机器人的空间机器人环境的更常见的量化表示方式相关。我将提出将不同形式的表达方式进行组合以实现富有成效的互动的方式。我将讨论针对不同任务和目的的各种形式的代表形式的优缺点。在演讲中,我将用定性表示形式介绍空间推理的示例,并说明这些表示形式的重要性质。导航任务将作为可能不希望进行详细定量计划的任务的示例。尽管从某种意义上说,定性表示比定量表示更抽象,但在另一种意义上,它们更具体,因为它们保持了与空间认知有关的时空事件的重要结构特性。这就提出了空间表示的“认知适当性”问题,我将在我的演讲中也要解决。这也提出了定性分析与定量分析各自表达能力的问题。最后,我的演讲将探讨代表空间知识的空间形式和语言形式之间的关系,例如,地图和空间的文字描述:它们可以被视为交流知识的替代或补充方式,每种方式都有其特定的优势。

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