Parameters
Configure allocation parameters using the radar chart
Scenarios
No scenarios loaded. Click "Add Examples" or run a simulation.
Thresholds
Mode Thresholds T(r)
AI Zone: r < b₁ (0.30)
Hybrid Zone: b₁ ≤ r < b₂ (0.70)
Human Zone: r ≥ b₂
Precision (π̃) has sign constraint wπ ≤ 0: high values favor AI automation.
Unified Score Function: The five ACF dimensions form a state vector x = (U, N, W, π̃, ε̃) ∈ [0,1]⁵.
The unified score r(x;θ) = σ(Σwiφi + Σwijφij) determines allocation via thresholds T(r) = AI if r < b₁, Hybrid if b₁ ≤ r < b₂, Human if r ≥ b₂.
Normalizations: Each dimension uses specialized normalization — U uses αt-weighted sigmoid, N uses log-sum-exp aggregation, W uses weighted max, π̃ and ε̃ use simple sigmoid normalization X̃ = X/(X+X₀).
Interactive: Drag the points on the chart to adjust dimension values and see how allocation mode changes.
Note: Precision has sign constraint wπ ≤ 0, meaning higher precision reduces human involvement (favors automation).
Normalizations: Each dimension uses specialized normalization — U uses αt-weighted sigmoid, N uses log-sum-exp aggregation, W uses weighted max, π̃ and ε̃ use simple sigmoid normalization X̃ = X/(X+X₀).
Interactive: Drag the points on the chart to adjust dimension values and see how allocation mode changes.
Note: Precision has sign constraint wπ ≤ 0, meaning higher precision reduces human involvement (favors automation).