Real and apparent biological inspiration in cognitive architectures

Holland, Owen; Diamond, Alan; Marques, Hugo Gravato; Mitra, Bhargav; Devereux, David

doi:10.1016/j.bica.2012.07.008

Cited by 7 publications

(5 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If a model is to be used then it is essential that one considers as many aspects as possible before arriving at a prediction or summing a conclusion. Modelling human behaviour is certainly a beneficial means of assessing a hypothesis, but it is wise to attempt an architecture that fits aspects of human cognition when using agent-based systems (Trafton et al, 2013;Holland et al, 2013). It is clear that agent-based systems can be useful for modelling some behaviours, but care is needed when stepping beyond the real limitations that they possess.…”

Section: Discussionmentioning

confidence: 99%

Organisational plasticity: can we really model human–agent behaviours?

Richards

2020

EBHRM

View full text Add to dashboard Cite

PurposeThe ability for an organisation to adapt and respond to external pressures is a beneficial activity towards optimising efficiency and increasing the likelihood of achieving set goals. It can also be suggested that this very ability to adapt to one's surroundings is one of the key factors of resilience. The nature of dynamically responding to sudden change and then to return to a state that is efficient may be termed as possessing the characteristic of plasticity. Uses of agent-based systems in assisting in organisational processes may have a hand in facilitating an organisations' plasticity, and computational modelling has often been used to try and predict both agent and human behaviour. Such models also promise the ability to examine the dynamics of organisational plasticity through the direct manipulation of key factors. This paper discusses the use of such models in application to organisational plasticity and in particular the relevance to human behaviour and perception of agent-based modelling. The uses of analogies for explaining organisational plasticity is also discussed, with particular discussion around the use of modelling. When the authors consider the means by which the authors can adopt theories to explain this type of behaviour, models tend to focus on aspects of predictability. This in turn loses a degree of realism when we consider the complex nature of human behaviour, and more so that of human–agent behaviour.Design/methodology/approachThe methodology and approach used for this paper is reflected in the review of the literature and research.FindingsThe use of human–agent behaviour models in organisational plasticity is discussed in this paper.Originality/valueThe originality of this paper is based on the importance of considering the human–agent-based models. When compared to agent-based model approaches, analogy is used as a narrative in this paper.

show abstract

Section: Discussionmentioning

confidence: 99%

Organisational plasticity: can we really model human–agent behaviours?

Richards

2020

EBHRM

View full text Add to dashboard Cite

show abstract

“…In the context of bioinspired cognitive architectures, it is important to discuss about the level of biological contribution to the development of processes and computational agents, which essentially constitute an architecture (Holland et al 2013).…”

Section: Methodological Aspectsmentioning

confidence: 99%

Methodological aspects for cognitive architectures construction: a study and proposal

et al. 2020

View full text Add to dashboard Cite

In the field of Artificial Intelligence (AI), efforts to achieve human-like behavior have taken very different paths through time. Cognitive Architectures (CAs) differentiate from traditional AI approaches, due to their intention to model cognitive and behavioral processes by understanding the brain’s structure and their functionalities in a natural way. However, the development of distinct CAs has not been easy, mainly because there is no consensus on the theoretical basis, assumptions or even purposes for their creation nor how well they reflect human function. In consequence, there is limited information about the methodological aspects to construct this type of models. To address this issue, some initial statements are established to contextualize about the origins and directions of cognitive architectures and their development, which help to outline perspectives, approaches and objectives of this work, supported by a brief study of methodological strategies and historical aspects taken by some of the most relevant architectures to propose a methodology which covers general perspectives for the construction of CAs. This proposal is intended to be flexible, focused on use-case tasks, but also directed by theoretic paradigms or manifestos. A case study between cognitive functions is then detailed, using visual perception and working memory to exemplify the proposal’s assumptions, postulates and binding tools, from their meta-architectural conceptions to validation. Finally, the discussion addresses the challenges found at this stage of development and future work directions.

show abstract

“…For example, Trafton et al (2013) proposed a cognitive architecture that would capture human interaction and then apply it to human-agent behaviours. This may also be applied to more complex cognitive behaviours that humans display and then translated into a cognitive architecture that takes HRI into account (Holland et al, 2013). Of course, the extent to which a robot system can utilise such a cognitive architecture is limited to the sensor fit associated with the individual robot.…”

Section: Human-robot Interactionmentioning

confidence: 99%

Escape from the factory of the robot monsters: agents of change

Richards

2017

TPM

View full text Add to dashboard Cite

Purpose-The increasing use of robotics within modern factories and workplaces not only sees us becoming more dependent on this technology but it also introduces innovative ways by which humans interact with complex systems. As agent-based systems become more integrated into work environments, the traditional human team becomes more integrated with agent-based automation and, in some cases, autonomous behaviours. This paper discusses these interactions in terms of team composition and how a human-agent collective can share goals via the delegation of authority between human and agent team members. Design/methodology/approach-This paper highlights the increasing integration of robotics in everyday life and examines the nature of how new novel teams may be constructed with the use of intelligent systems and autonomous agents. Findings-Areas of human factors and human-computer interaction are used to discuss the benefits and limitations of human-agent teams. Research limitations/implications-There is little research in (human-robot) (H-R) teamwork, especially from a human factors perspective. Practical implications-Advancing the author's understanding of the H-R team (and associated intelligent agent systems) will assist in the integration of such systems in everyday practices. Social implications-H-R teams hold a great deal of social and organisational issues that need further exploring. Only through understanding this context can advanced systems be fully realised. Originality/value-This paper is multidisciplinary, drawing on areas of psychology, computer science, robotics and human-computer Interaction. Specific attention is given to an emerging field of autonomous software agents that are growing in use. This paper discusses the uniqueness of the human-agent teaming that results when human and agent members share a common goal within a team.

show abstract

Real and apparent biological inspiration in cognitive architectures

Cited by 7 publications

References 39 publications

Organisational plasticity: can we really model human–agent behaviours?

Organisational plasticity: can we really model human–agent behaviours?

Methodological aspects for cognitive architectures construction: a study and proposal

Escape from the factory of the robot monsters: agents of change

Contact Info

Product

Resources

About