A unifying computational model of decision making
نویسندگان
چکیده
منابع مشابه
How Prior Probability Influences Decision Making: A Unifying Probabilistic Model
How does the brain combine prior knowledge with sensory evidence when making decisions under uncertainty? Two competing descriptive models have been proposed based on experimental data. The first posits an additive offset to a decision variable, implying a static effect of the prior. However, this model is inconsistent with recent data from a motion discrimination task involving temporal integr...
متن کاملComputational modeling of dynamic decision making using connectionist networks
In this research connectionist modeling of decision making has been presented. Important areas for decision making in the brain are thalamus, prefrontal cortex and Amygdala. Connectionist modeling with 3 parts representative for these 3 areas is made based the result of Iowa Gambling Task. In many researches Iowa Gambling Task is used to study emotional decision making. In these kind of decisio...
متن کاملMoralDM: A Computational Model of Moral Decision-Making
We present a cognitively motivated model of moral decisionmaking, MoralDM, which models psychological findings about utilitarian and deontological modes of reasoning. Current theories of moral decision-making extend beyond pure utilitarian models by including contextual factors that vary culturally. Our model employs both first-principles reasoning and analogical reasoning to implement rules of...
متن کاملA Computational Model of Commonsense Moral Decision Making
We introduce a new computational model of moral decision making, drawing on a recent theory of commonsense moral learning via social dynamics. Our model describes moral dilemmas as utility function that computes trade-offs in values over abstract moral dimensions, which provide interpretable parameter values when implemented in machineled ethical decision-making. Moreover, characterizing the so...
متن کاملA decision-making Fokker-Planck model in computational neuroscience.
In computational neuroscience, decision-making may be explained analyzing models based on the evolution of the average firing rates of two interacting neuron populations, e.g., in bistable visual perception problems. These models typically lead to a multi-stable scenario for the concerned dynamical systems. Nevertheless, noise is an important feature of the model taking into account both the fi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Cognitive Processing
سال: 2019
ISSN: 1612-4782,1612-4790
DOI: 10.1007/s10339-019-00904-3