June 2019

Social Action in Socially Situated Agents

Posted on June 16, 2019 by Conference Paper Publication

Chloe M. Barnes, Anikó Ekárt, Peter R. Lewis: Social Action in Socially Situated Agents. In: Proceedings of the IEEE 13th International Conference on Self-Adaptive and Self-Organizing Systems (SASO), pp. 97–106, IEEE, 2019.

Abstract

Two systems pursuing their own goals in a shared world can interact in ways that are not so explicit - such that the presence of another system alone can interfere with how one is able to achieve its own goals. Drawing inspiration from human psychology and the theory of social action, we propose the notion of employing social action in socially situated agents as a means of alleviating interference in interacting systems. Here we demonstrate that these specific issues of behavioural and evolutionary instability caused by the unintended consequences of interactions can be addressed with agents capable of a fusion of goal-rationality and traditional action, resulting in a stable society capable of achieving goals during the course of evolution.


BibTeX (Download)

@inproceedings{Barnes2019saso,
title = {Social Action in Socially Situated Agents},
author = {Chloe M. Barnes and Anikó Ekárt and Peter R. Lewis},
url = {https://ieeexplore.ieee.org/document/8780530},
doi = {10.1109/SASO.2019.00021},
year  = {2019},
date = {2019-06-19},
urldate = {2019-01-01},
booktitle = {Proceedings of the IEEE 13th International Conference on Self-Adaptive and Self-Organizing Systems (SASO)},
pages = {97--106},
publisher = {IEEE},
abstract = {Two systems pursuing their own goals in a shared world can interact in ways that are not so explicit - such that the presence of another system alone can interfere with how one is able to achieve its own goals. Drawing inspiration from human psychology and the theory of social action, we propose the notion of employing social action in socially situated agents as a means of alleviating interference in interacting systems. Here we demonstrate that these specific issues of behavioural and evolutionary instability caused by the unintended consequences of interactions can be addressed with agents capable of a fusion of goal-rationality and traditional action, resulting in a stable society capable of achieving goals during the course of evolution.},
keywords = {Agent-Based Systems, ANNs, Artificial Life, Evolutionary Algorithms, Neuroevolution, River Crossing, Social Action},
pubstate = {published},
tppubtype = {inproceedings}
}

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

Posted on June 16, 2019 by Publication Workshop Paper

Chloe M. Barnes, Kirstie Bellman, Jean Botev, Ada Diaconescu, Lukas Esterle, Christian Gruhl, Chris Landauer, Peter R. Lewis, Phyllis R. Nelson, Anthony Stein, Christopher Stewart, Sven Tomforde: CHARIOT -- Towards a Continuous High-Level Adaptive Runtime Integration Testbed. In: Proceedings of the IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W), pp. 52–55, IEEE, 2019.

Abstract

Integrated networked systems sense a common environment, learn to navigate the environment and share their experiences. Sharing experiences simplifies learning, reducing costly trial and error in complex environments. However, integration produces dependencies that make constituent systems less robust to failures, unexpected outputs and performance anomalies. Even with APIs and reflective, self-aware techniques, system integration still requires expert programming and tuning. Self-integrating systems proposed in recent research automate integration, but can be challenging to validate at scale. We therefore propose CHARIOT, a common test environment to allow for different approaches and systems to be deployed, assessed and compared on a shared platform for the development of self-integrating systems. In this paper, we discuss the underlying requirements and challenges, potential metrics, and a system metamodel to accommodate these.


BibTeX (Download)

@inproceedings{Barnes2019CHARIOTTestbed,
title = {CHARIOT -- Towards a Continuous High-Level Adaptive Runtime Integration Testbed},
author = {Chloe M. Barnes and Kirstie Bellman and Jean Botev and Ada Diaconescu and Lukas Esterle and Christian Gruhl and Chris Landauer and Peter R. Lewis and Phyllis R. Nelson and Anthony Stein and Christopher Stewart and Sven Tomforde},
url = {https://ieeexplore.ieee.org/document/8791947},
doi = {10.1109/FAS-W.2019.00026},
year  = {2019},
date = {2019-06-19},
urldate = {2019-01-01},
booktitle = {Proceedings of the IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W)},
pages = {52--55},
publisher = {IEEE},
abstract = {Integrated networked systems sense a common environment, learn to navigate the environment and share their experiences. Sharing experiences simplifies learning, reducing costly trial and error in complex environments. However, integration produces dependencies that make constituent systems less robust to failures, unexpected outputs and performance anomalies. Even with APIs and reflective, self-aware techniques, system integration still requires expert programming and tuning. Self-integrating systems proposed in recent research automate integration, but can be challenging to validate at scale. We therefore propose CHARIOT, a common test environment to allow for different approaches and systems to be deployed, assessed and compared on a shared platform for the development of self-integrating systems. In this paper, we discuss the underlying requirements and challenges, potential metrics, and a system metamodel to accommodate these.},
keywords = {Adaptive Systems, Runtime Systems Integration},
pubstate = {published},
tppubtype = {inproceedings}
}

“When You Believe in Things That You Don’t Understand”: The Effect of Cross-Generational Habits on Self-Improving System Integration

Posted on June 16, 2019 by Publication Workshop Paper

Chloe M. Barnes, Lukas Esterle, John N. A. Brown: ``When You Believe in Things That You Don't Understand. In: Proceedings of the IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W), pp. 28–31, IEEE, 2019.

Abstract

Humans experiencing unexpected feedback to certain actions which they are not able to explain, might develop superstitious behaviour. In this paper, we discuss that similar behaviour might also occur in engineered systems. We provide a thought-experiment regarding such behaviour in computational systems. In this paper, we propose a first step towards improved runtime systems integration based on a the ability to become aware of previously-unknown others and their actions, as described in networked self-awareness.


BibTeX (Download)

@inproceedings{Barnes2019SISSY,
title = {``When You Believe in Things That You Don't Understand},
author = {Chloe M. Barnes and Lukas Esterle and John N. A. Brown},
url = {https://ieeexplore.ieee.org/abstract/document/8791979},
doi = {10.1109/FAS-W.2019.00020},
year  = {2019},
date = {2019-06-16},
urldate = {2019-01-01},
booktitle = {Proceedings of the IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W)},
pages = {28--31},
publisher = {IEEE},
abstract = {Humans experiencing unexpected feedback to certain actions which they are not able to explain, might develop superstitious behaviour. In this paper, we discuss that similar behaviour might also occur in engineered systems. We provide a thought-experiment regarding such behaviour in computational systems. In this paper, we propose a first step towards improved runtime systems integration based on a the ability to become aware of previously-unknown others and their actions, as described in networked self-awareness.},
keywords = {Computational Superstition, Networked Self-Awareness, Runtime Systems Integration, Self-Awareness},
pubstate = {published},
tppubtype = {inproceedings}
}