Dynamic Architectures for Computational Self-Awareness

计算自我意识的动态架构

• 批准号: 1926505
• 金额: --
• 依托单位: Aston University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-1926505
• 关键词: Dynamic; Architectures; Computational; Self; Awareness

There has been growing interest in recent years regarding the exploration of technical systems andhow they can express autonomous behaviour as a way of addressing a wide range of challenges;modern systems are being used in increasingly diverse, unpredictable and dynamic environments,creating a need for systems to overcome unknown states and situations through reasoning andlearning - without human intervention. As the environments and the goals of the systems are morecommonly subject to change over time, it is becoming impossible for programmers to know the"correct" approach to solving run-time problems whilst designing the systems themselves; it istherefore increasingly important for systems to have the ability to autonomously adapt to respondto these changes in an effective and efficient manner. One such approach to tackling these issues is designing systems with computational self-awareness capabilities, so they can learn and act withoutany prior knowledge, whilst extending their skills over time.With this in mind, this project therefore aims to look at how self-aware computing systems can bedesigned to operate in an ever-changing environment, specifically looking at the additionalcomplexity of interactions between systems and how these can be engineered to be efficient andmeaningful. Further, the focus is on system to system interactions, rather than the larger area ofsociotechnical systems where there are complex interactions between systems and humans alike.One question this project aims to address surrounds how systems are able to learn and achieve theirown goals in an environment where their own actions are affected by another - either implicitly or explicitly. Researchers have asked questions about issues of integration which considers explicitissues in the design of the system itself; this project however aims to investigate the unintendedinteractions that may arise between two interacting systems, and how systems can be designed tocombat these issues autonomously. This involves consideration of how one models both itself andothers, and how these so-called "social systems" are able to develop a deeper understanding of their place in the world around them, as well as the impact others can have on themselves. Theories of human psychology and sociology will be used as inspiration to answer these questions.A further question that arises from this regards the learning processes themselves that a system can exhibit, and how these relate to the context systems operate in. For example, the outcome of a certain behaviour can change depending on the context/situation; if the system is not complex enough to perceive the cause of this change (i.e. the actions of another, a change in the environment), it will appear to the system that there is no reason for this change, resulting in the system changing its knowledge accordingly. A consequence of this is that well-learnt and successful knowledge and behaviour may be changed or lost due to unknown interactions. This project therefore also aims to investigate whether the learning processes of systems can be modularised, such that contextual change does not interfere with learnt knowledge. This way, systems may be able to interact more effectively due to a more robust learning approach.

近年来，人们对探索技术系统以及它们如何表达自主行为作为应对各种挑战的一种方式越来越感兴趣;现代系统正在日益多样化，不可预测和动态的环境中使用，需要系统通过推理和学习来克服未知的状态和情况-没有人为干预。由于环境和系统的目标越来越容易随着时间的推移而改变，程序员在设计系统的同时不可能知道解决运行时问题的“正确”方法;因此，系统具有自主适应能力以有效和高效的方式响应这些变化变得越来越重要。解决这些问题的方法之一是设计具有计算自我意识能力的系统，这样他们就可以在没有任何先验知识的情况下学习和行动，同时随着时间的推移扩展他们的技能。考虑到这一点，这个项目因此旨在研究如何设计自我意识计算系统，以便在不断变化的环境中运行，特别是研究系统之间交互的额外复杂性，以及如何将这些设计成高效和有意义的。此外，重点是系统与系统的交互，而不是更大范围的社会技术系统，在那里系统和人类之间存在复杂的交互。这个项目旨在解决的一个问题是，系统如何能够在一个自身行为受到另一个系统影响的环境中学习和实现自己的目标-无论是隐性的还是显性的。研究人员提出了一些关于整合问题的问题，这些问题在系统本身的设计中考虑了明确的组织;然而，这个项目的目的是调查两个相互作用的系统之间可能出现的无意的相互作用，以及如何设计系统来自主地解决这些问题。这涉及到一个人如何塑造自己和他人，以及这些所谓的“社会系统”如何能够更深入地理解他们在周围世界中的位置，以及其他人对自己的影响。人类心理学和社会学的理论将被用作回答这些问题的灵感。由此产生的另一个问题是关于系统可以展示的学习过程本身，以及这些过程如何与系统运行的上下文相关。例如，某种行为的结果可能会根据上下文/情况而改变;如果系统不够复杂，无法感知这种变化的原因（即另一个人的行为，环境的变化），那么系统会认为这种变化没有原因，导致系统相应地改变其知识。这样做的后果是，由于未知的相互作用，学习良好和成功的知识和行为可能会改变或丢失。因此，该项目还旨在研究系统的学习过程是否可以模块化，以便上下文的变化不会干扰学习知识。这样，由于更强大的学习方法，系统可以更有效地交互。

项目成果

Beyond goal-rationality: Traditional action can reduce volatility in socially situated agents

• DOI: 10.1016/j.future.2020.07.033
• 发表时间: 2020-12-01
• 期刊: FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
• 影响因子: 7.5
• 作者: Barnes，Chloe M.;Ekart，Aniko;Lewis，Peter R.
• 通讯作者: Lewis，Peter R.

CHARIOT - Towards a Continuous High-Level Adaptive Runtime Integration Testbed

CHIOT - 迈向持续的高级自适应运行时集成测试平台

• DOI: 10.1109/fas-w.2019.00026
• 发表时间: 2019
• 作者: Barnes C

Coevolutionary Learning of Neuromodulated Controllers for Multi-Stage and Gamified Tasks

• DOI: 10.1109/acsos49614.2020.00034
• 发表时间: 2020-08
• 期刊: 2020 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS)
• 作者: Chloe M. Barnes;Anikó Ekárt;K. Ellefsen;K. Glette;Peter R. Lewis;J. Tørresen

"When you Believe in Things that you don't Understand": the Effect of Cross-Generational Habits on Self-Improving System Integration

“当你相信你不理解的事情时”：跨代习惯对自我改进系统集成的影响

• DOI: 10.1109/fas-w.2019.00020
• 发表时间: 2019
• 作者: Barnes C

Social Action in Socially Situated Agents

• DOI: 10.1109/saso.2019.00021
• 发表时间: 2019-06
• 期刊: 2019 IEEE 13th International Conference on Self-Adaptive and Self-Organizing Systems (SASO)
• 作者: Chloe M. Barnes;Anikó Ekárt;Peter R. Lewis