Abstract—We study collective decision-making in a model of human groups, with network interactions, performing two alternative choice tasks. We focus on the speed-accuracy tradeoff, i.e., the tradeoff between a quick decision and a reliable decision, for individuals in the network. We model the evidence aggrega-tion process across the network using a coupled drift diffusion model (DDM) and consider the free response paradigm in which individuals take their time to make the decision. We develop reduced DDMs as decoupled approximations to the coupled DDM and characterize their efficiency. We determine high probability bounds on the error rate and the expected decision time for the reduced DDM. We show the effect of the decision-maker’s locati...
We consider neurally-based models for decision-making in the presence of noisy incoming data. The tw...
People are usually brought together in a social network to make synergetic decisions. This decision ...
On the basis of detailed analysis of reaction times and neurophysiological data from tasks involving...
Abstract—We study collective decision-making in a model of human groups, with network interactions, ...
Abstract — This paper investigates the effect of coupling in a collective decision-making scenario, ...
The modeling and prediction of collective human behavior has been one of the key challenges of socia...
We review how leaky competing accumulators (LCAs) can be used to model decision making in two-altern...
This paper studies prototypical strategies to sequentially aggregate independent decisions. We consi...
With a principled methodology for systematic design of human–robot decision-making teams as a motiva...
In principle, formal dynamical models of decision making hold the potential to represent fundamental...
Achieving fast and accurate collective decisions with a large number of simple agents without relyin...
It is common for biological networks to encounter situations where agents need to decide between mul...
A class of binary decision-making tasks called the two-alternative forced-choice task has been used ...
Modeling and analysis of human behaviors in social networks are essential in fields such as online b...
We investigate how the network topology of social networks impacts decision making. First we look at...
We consider neurally-based models for decision-making in the presence of noisy incoming data. The tw...
People are usually brought together in a social network to make synergetic decisions. This decision ...
On the basis of detailed analysis of reaction times and neurophysiological data from tasks involving...
Abstract—We study collective decision-making in a model of human groups, with network interactions, ...
Abstract — This paper investigates the effect of coupling in a collective decision-making scenario, ...
The modeling and prediction of collective human behavior has been one of the key challenges of socia...
We review how leaky competing accumulators (LCAs) can be used to model decision making in two-altern...
This paper studies prototypical strategies to sequentially aggregate independent decisions. We consi...
With a principled methodology for systematic design of human–robot decision-making teams as a motiva...
In principle, formal dynamical models of decision making hold the potential to represent fundamental...
Achieving fast and accurate collective decisions with a large number of simple agents without relyin...
It is common for biological networks to encounter situations where agents need to decide between mul...
A class of binary decision-making tasks called the two-alternative forced-choice task has been used ...
Modeling and analysis of human behaviors in social networks are essential in fields such as online b...
We investigate how the network topology of social networks impacts decision making. First we look at...
We consider neurally-based models for decision-making in the presence of noisy incoming data. The tw...
People are usually brought together in a social network to make synergetic decisions. This decision ...
On the basis of detailed analysis of reaction times and neurophysiological data from tasks involving...