ExpectedUtility

ExpectedUtility constructs a model object for expected utility theory

• α: utility curvature for gains

Constructor

ExpectedUtility(;α=.80)

Gamble(;p=[.5,.5], v=[10.0,0.0])

Constructs a gamble object with probability vector p and outcome vector v.

Fields

• p: probability vector
• v: outcome vector

ProspectTheory(;α=.80, β=α, γg=.70, γl=γg, λ=2.25)

Constructs a model object for cummulative prospect theory. By default, parameters for utility curvature and probability weigting are equal gains and losses.

Fields

• α=.80: utility curvature for gains
• β=α: utility curvature for losses
• γg=.70: probability weighting parameter for gains
• γl=γg: probability weighting parameter for losses
• λ=2.25: loss aversion parameter

References

Fennema, H., & Wakker, P. (1997). Original and cumulative prospect theory: A discussion of empirical differences. Journal of Behavioral Decision Making, 10(1), 53-64.

Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and uncertainty, 5(4), 297-323.

TAX(;δ=.80, β=.3, γ=.70)

Constructs a model object for transfer of attention exchange.

Fields

• δ=1.0: transfer of attention parameter
• γ=1.0: probability weighting parameter
• β=.70: utility curvature

References

Birnbaum, M. H., & Chavez, A. (1997). Tests of theories of decision making: Violations of branch independence and distribution independence. Organizational Behavior and Human Decision Processes, 71(2), 161-194. Birnbaum, M. H. (2008). New paradoxes of risky decision making. Psychological Review, 115(2), 463.

UtilityModel

UtilityModel is an abstract utility-based model object ````

ValenceExpectancy

ValenceExpectancy constructs a model object for expected utility theory

• υ: a vector of expected utilities
• Δ: learning rate where Δ ∈ [0,1]
• α: utility shape parameter where α > 0
• λ: loss aversion where λ > 0
• c: temperature

mean(model::TAX, gamble::Gamble)

Computes mean utility for the TAX model

Arguments

• model: a model M <: UtilityModel
• gamble: a gamble object

mean

mean generic method for computing mean

• model: a model M <: UtilityModel
• gamble: a gamble object

Function Signature

mean(model::UtilityModel, gamble::Gamble)

std(model::UtilityModel, gamble::Gamble)

std a generic method for computing the standard deviation of the gamble

• model: a model M <: UtilityModel
• gamble: a gamble object

var(model::UtilityModel, gamble::Gamble)

var a generic method for computing the variance of the gamble

• model: a model M <: UtilityModel
• gamble: a gamble object

_compute_weights(p, γ)

Computes decision weights based on cummulative outcomes

Arguments

• p: a probability vector
• γ: parameter that controls weighting of low and high probabilities

compute_utility

compute_utility computes utility of gamble outcomes according to expected utility theory

• model: a model object for prospect theory
• gamble: a gamble object

Function Signature

compute_utility(model::ExpectedUtility, gamble::Gamble)

compute_utility(model::ProspectTheory, gamble)

Computes utility of gamble outcomes according to prospect theory

Arguments

• model: a model object for prospect theory
• gamble: a gamble object

compute_utility(model::TAX, gamble)

Computes utility of gamble outcomes according to TAX

Arguments

• model: a model object for TAX
• gamble: a gamble object

compute_utility(model::ValenceExpectancy, outcomes::Vector)

compute_utility computes utility of gamble outcomes according to expected utility theory

• model: a model object for prospect theory
• gamble: a gamble object

Function Signature

compute_utility(model::ExpectedUtility, gamble::Gamble)

compute_weights(model::ProspectTheory, gamble::Gamble)

Computes decision weights based on cummulative outcomes

Arguments

• model: a model object for prospect theory
• gamble: a gamble object

compute_weights(model::UtilityModel, gamble::Gamble)

compute_weights a generic method for computing decision weights

• model: a model M <: UtilityModel
• gamble: a gamble object

sort!(model::UtilityModel, gamble)

sort! a generic method for sorting gamble probabilities and values. The generic method does not sort the gambles

• model: a model
• gamble: a gamble object