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A Co-flow Structure for Goal-Directed Internal Change.

ABSTRACT: We describe a co-flow structure that models internal, goal-directed changes to an attribute (e.g., employee loyalty) of fundamental material (e.g., employees). This co-flow accommodates problems not adequately modeled with an existing, generic structure. Our structure builds on the co-flow proposed by Hines, which uses an information delay to model external change to an attribute. We use a first-order information delay to model both external changes to the attribute from the material stock and internal changes from an internal goal for the attribute. We provide an exact, dynamic solution for this co-flow enabling us to precisely describe its equilibrium and non-equilibrium behavior. Several examples are provided and discussed, including a situation where a management program is designed to increase average employee loyalty. In addition, we review applications of traditional and Hines co-flow structures to provide background and to describe our evolutionary path towards design of the new co-flow.

SUBMITTER: Gambardella P

PROVIDER: S-EPMC5720161 | biostudies-literature | 2017 Jan-Mar

REPOSITORIES: biostudies-literature

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A Co-flow Structure for Goal-Directed Internal Change.

Gambardella Pascal P Polk Deborah E DE Lounsbury David D Levine Ralph R

System dynamics review 20170101 1

We describe a co-flow structure that models internal, goal-directed changes to an attribute (e.g., employee loyalty) of fundamental material (e.g., employees). This co-flow accommodates problems not adequately modeled with an existing, generic structure. Our structure builds on the co-flow proposed by Hines, which uses an information delay to model external change to an attribute. We use a first-order information delay to model both external changes to the attribute from the material stock and i ...[more]

PMID: 29225415

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Project description:From social dining in households to product assembly in manufacturing lines, goal-directed reasoning and cooperation with other agents in shared workspaces is a ubiquitous aspect of our day-to-day activities. Critical for such behaviours is the ability to spontaneously anticipate what is doable by oneself as well as the interacting partner based on the evolving environmental context and thereby exploit such information to engage in goal-oriented action sequences. In the setting of an industrial task where two robots are jointly assembling objects in a shared workspace, we describe a bioinspired neural architecture for goal-directed action planning based on coupled interactions between multiple internal models, primarily of the robot's body and its peripersonal space. The internal models (of each robot's body and peripersonal space) are learnt jointly through a process of sensorimotor exploration and then employed in a range of anticipations related to the feasibility and consequence of potential actions of two industrial robots in the context of a joint goal. The ensuing behaviours are demonstrated in a real-world industrial scenario where two robots are assembling industrial fuse-boxes from multiple constituent objects (fuses, fuse-stands) scattered randomly in their workspace. In a spatially unstructured and temporally evolving assembly scenario, the robots employ reward-based dynamics to plan and anticipate which objects to act on at what time instances so as to successfully complete as many assemblies as possible. The existing spatial setting fundamentally necessitates planning collision-free trajectories and avoiding potential collisions between the robots. Furthermore, an interesting scenario where the assembly goal is not realizable by either of the robots individually but only realizable if they meaningfully cooperate is used to demonstrate the interplay between perception, simulation of multiple internal models and the resulting complementary goal-directed actions of both robots. Finally, the proposed neural framework is benchmarked against a typically engineered solution to evaluate its performance in the assembly task. The framework provides a computational outlook to the emerging results from neurosciences related to the learning and use of body schema and peripersonal space for embodied simulation of action and prediction. While experiments reported here engage the architecture in a complex planning task specifically, the internal model based framework is domain-agnostic facilitating portability to several other tasks and platforms.

Project description:IntroductionHarmful behavior such as smoking may reflect a disturbance in the balance of goal-directed and habitual control. Animal models suggest that habitual control develops after prolonged substance use. In this study, we investigated whether smokers (N = 49) differ from controls (N = 46) in the regulation of goal-directed and habitual behavior. It was also investigated whether individual differences in nicotine dependence levels were associated with habitual responding.MethodsWe used two different multistage instrumental learning tasks that consist of an instrumental learning phase, subsequent outcome devaluation, and a testing phase to measure the balance between goal-directed and habitual responding. The testing phases of these tasks occurred after either appetitive versus avoidance instrumental learning. The appetitive versus aversive instrumental learning stages in the two different tasks modeled positive versus negative reinforcement, respectively.ResultsSmokers and nonsmoking controls did not differ on habitual versus goal-directed control in either task. Individual differences in nicotine dependence within the group of smokers, however, were positively associated with habitual responding after appetitive instrumental learning. This effect seems to be due to impaired stimulus-outcome learning, thereby hampering goal-directed task performance and tipping the balance to habitual responding.ConclusionsThe current finding highlights the importance of individual differences within smokers. For future research, neuroimaging studies are suggested to further unravel the nature of the imbalance between goal-directed versus habitual control in severely dependent smokers by directly measuring activity in the corresponding brain systems.ImplicationsGoal-directed versus habitual behavior in substance use and addiction is highly debated. This study investigated goal-directed versus habitual control in smokers. The findings suggest that smokers do not differ from controls in goal-directed versus habitual control. Individual differences in nicotine dependence within smokers, however, were positively associated with habitual responding after appetitive instrumental learning. This effect seems to be due to impaired stimulus-outcome learning, thereby hampering goal-directed task performance and tipping the balance to habitual responding. These findings add to the ongoing debate on habitual versus goal-directed control in addiction and emphasize the importance of individual differences within smokers.

Dataset Information

A Co-flow Structure for Goal-Directed Internal Change.

Publications

A Co-flow Structure for Goal-Directed Internal Change.

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