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Combining Computational and Social Effort for Collaborative Problem Solving.

Wagy MD, Bongard JC - PLoS ONE (2015)

Bottom Line: In this study, we demonstrate the conditions under which such synergy can arise.We show that, for a design task, three elements are sufficient: humans apply intuitions to the problem, algorithms automatically determine and report back on the quality of designs, and humans observe and innovate on others' designs to focus creative and computational effort on good designs.This study suggests how such collaborations should be composed for other domains, as well as how social and computational dynamics mutually influence one another during collaborative problem solving.

View Article: PubMed Central - PubMed

Affiliation: University of Vermont, Computer Science Department, Burlington, Vermont, United States of America.

ABSTRACT
Rather than replacing human labor, there is growing evidence that networked computers create opportunities for collaborations of people and algorithms to solve problems beyond either of them. In this study, we demonstrate the conditions under which such synergy can arise. We show that, for a design task, three elements are sufficient: humans apply intuitions to the problem, algorithms automatically determine and report back on the quality of designs, and humans observe and innovate on others' designs to focus creative and computational effort on good designs. This study suggests how such collaborations should be composed for other domains, as well as how social and computational dynamics mutually influence one another during collaborative problem solving.

No MeSH data available.


Screen-shot of the user interface with components.Enclosed in the yellow box is the history panel (a); in green, the simulation panel (b); and in blue, the design panel (c).
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pone.0142524.g002: Screen-shot of the user interface with components.Enclosed in the yellow box is the history panel (a); in green, the simulation panel (b); and in blue, the design panel (c).

Mentions: Each participant was instructed to design a robot that could move as far as possible in the simulation. Participants accomplished this by designing a robot in the design panel (Fig 2c), which was initially blank. They could then command a search algorithm to find good controllers for that robot. The quality of a controller is defined by how far it enables the robot to move from its starting position in fifteen seconds of simulation time. They could watch the progress of this optimization process in the simulation panel (Fig 2b). Members of the IMT could see their own past designs in the history panel (Fig 2a), while members of the CMT could see designs produced by themselves and other participants in the same panel. It was through this history panel that users ‘communicated’ designs to other participants.


Combining Computational and Social Effort for Collaborative Problem Solving.

Wagy MD, Bongard JC - PLoS ONE (2015)

Screen-shot of the user interface with components.Enclosed in the yellow box is the history panel (a); in green, the simulation panel (b); and in blue, the design panel (c).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4636355&req=5

pone.0142524.g002: Screen-shot of the user interface with components.Enclosed in the yellow box is the history panel (a); in green, the simulation panel (b); and in blue, the design panel (c).
Mentions: Each participant was instructed to design a robot that could move as far as possible in the simulation. Participants accomplished this by designing a robot in the design panel (Fig 2c), which was initially blank. They could then command a search algorithm to find good controllers for that robot. The quality of a controller is defined by how far it enables the robot to move from its starting position in fifteen seconds of simulation time. They could watch the progress of this optimization process in the simulation panel (Fig 2b). Members of the IMT could see their own past designs in the history panel (Fig 2a), while members of the CMT could see designs produced by themselves and other participants in the same panel. It was through this history panel that users ‘communicated’ designs to other participants.

Bottom Line: In this study, we demonstrate the conditions under which such synergy can arise.We show that, for a design task, three elements are sufficient: humans apply intuitions to the problem, algorithms automatically determine and report back on the quality of designs, and humans observe and innovate on others' designs to focus creative and computational effort on good designs.This study suggests how such collaborations should be composed for other domains, as well as how social and computational dynamics mutually influence one another during collaborative problem solving.

View Article: PubMed Central - PubMed

Affiliation: University of Vermont, Computer Science Department, Burlington, Vermont, United States of America.

ABSTRACT
Rather than replacing human labor, there is growing evidence that networked computers create opportunities for collaborations of people and algorithms to solve problems beyond either of them. In this study, we demonstrate the conditions under which such synergy can arise. We show that, for a design task, three elements are sufficient: humans apply intuitions to the problem, algorithms automatically determine and report back on the quality of designs, and humans observe and innovate on others' designs to focus creative and computational effort on good designs. This study suggests how such collaborations should be composed for other domains, as well as how social and computational dynamics mutually influence one another during collaborative problem solving.

No MeSH data available.