A Cognitive Architecture Based on Dual Process Theory

Strannegård, Claes; Haugwitz, Rickard von; Wessberg, Johan; Balkenius, Christian

doi:10.1007/978-3-642-39521-5_15

Cited by 11 publications

(4 citation statements)

References 24 publications

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“…As the dual-process theory architectures are iteratively analyzed (Augello, et al, 2017;Blythe, 2012;Dennis, et al, 2018;Lieto, et al, 2017;Potamianos, 2014;Strannegård, et al, 2013), some common themes become more apparent. System 1 and System 2 frequently represent low-level and high-level goal subsystems.…”

Section: Dual-process Theory Implementationsmentioning

confidence: 99%

Imitating human responses via a Dual-Process Model

Grimm

Peterson

Miller

2023

Cognitive Systems Research

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Section: Dual-process Theory Implementationsmentioning

confidence: 99%

Imitating human responses via a Dual-Process Model

Grimm

Peterson

Miller

2023

Cognitive Systems Research

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“…Cognitive architectures have been the subject of research for a long time, and different solutions have been proposed in order to provide artificial systems with human cognitive and behavioral characteristics [17][18][19]. Different approaches have been exploited, ranging from symbolic [20][21][22], emergent [23,24] and hybrid architectures [25,26]. The increasing utilization of robots in society determined a need to design architectures that also provide support for a broad range of HRI applications, where robots must share the same physical space [27], and they have to adapt the interaction to the users' needs, mental states and profiles [28][29][30].…”

Section: Cognitive Architecturesmentioning

confidence: 99%

Collaborative Autonomy: Human–Robot Interaction to the Test of Intelligent Help

Cantucci

Falcone

2022

Electronics

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A big challenge in human–robot interaction (HRI) is the design of autonomous robots that collaborate effectively with humans, exposing behaviors similar to those exhibited by humans when they interact with each other. Indeed, robots are part of daily life in multiple environments (i.e., cultural heritage sites, hospitals, offices, touristic scenarios and so on). In these contexts, robots have to coexist and interact with a wide spectrum of users not necessarily able or willing to adapt their interaction level to the kind requested by a machine: the users need to deal with artificial systems whose behaviors must be adapted as much as possible to the goals/needs of the users themselves, or more in general, to their mental states (beliefs, goals, plans and so on). In this paper, we introduce a cognitive architecture for adaptive and transparent human–robot interaction. The architecture allows a social robot to dynamically adjust its level of collaborative autonomy by restricting or expanding a delegated task on the basis of several context factors such as the mental states attributed to the human users involved in the interaction. This collaboration has to be based on different cognitive capabilities of the robot, i.e., the ability to build a user’s profile, to have a Theory of Mind of the user in terms of mental states attribution, to build a complex model of the context, intended both as a set of physical constraints and constraints due to the presence of other agents, with their own mental states. Based on the defined cognitive architecture and on the model of task delegation theorized by Castelfranchi and Falcone, the robot’s behavior is explainable by considering the abilities to attribute specific mental states to the user, the context in which it operates and its attitudes in adapting the level of autonomy to the user’s mental states and the context itself. The architecture has been implemented by exploiting the well known agent-oriented programming framework Jason. We provide the results of an HRI pilot study in which we recruited 26 real participants that have interacted with the humanoid robot Nao, widely used in HRI scenarios. The robot played the role of a museum assistant with the main goal to provide the user the most suitable museum exhibition to visit.

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“…In this line, different attempts have been made to introduce the tenets of the dual process models in the computational arena. Efforts have been made, for example, in the areas of knowledge representation and reasoning [21] [40], cognitive systems dealing with arithmetical calculations [50], action selection [20], cognitive models of emotions [38], question answering [39] and in the design of general purpose cognitive architectures, such as CLARION, whose principles are explicitly inspired by such a theoretical framework [51].…”

Section: Dual Process Approach and Computational Creativitymentioning

confidence: 99%

Artwork creation by a cognitive architecture integrating computational creativity and dual process approaches

Augello¹,

Infantino²,

Lieto

et al. 2016

Biologically Inspired Cognitive Architectures

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The paper proposes a novel cognitive architecture (CA) for computational creativity based on the Psi model and on the mechanisms inspired by dual process theories of reasoning and rationality. In recent years, many cognitive models have focused on dual process theories to better describe and implement complex cognitive skills in artificial agents, but creativity has been approached only at a descriptive level. In previous works we have described various modules of the cognitive architecture that allows a robot to execute creative paintings. By means of dual process theories we refine some relevant mechanisms to obtain artworks, and in particular we explain details about the resolution level of the CA dealing with different strategies of access to the Long Term Memory (LTM) and managing the interaction between S1 and S2 processes of the dual process theory. The creative process involves both divergent and convergent processes in either implicit or explicit manner. This leads to four activities (exploratory, reflective, tacit, and analytic) that, triggered by urges and motivations, generate creative acts. These creative acts exploit both the LTM and the WM in order to make novel substitutions to a perceived image by properly mixing parts of pictures coming from different domains. The paper highlights the role of the interaction between S1 and S2 processes, modulated by the resolution level, which focuses the attention of the creative agent by broadening or narrowing the exploration of novel solutions, or even drawing the solution from a set of already made associations. An example of artificial painter is described in some experimentations by using a robotic platform.

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A Cognitive Architecture Based on Dual Process Theory

Cited by 11 publications

References 24 publications

Imitating human responses via a Dual-Process Model

Imitating human responses via a Dual-Process Model

Collaborative Autonomy: Human–Robot Interaction to the Test of Intelligent Help

Artwork creation by a cognitive architecture integrating computational creativity and dual process approaches

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