feat: add default erroring anticipative solver generators (#74)

Author: BatyLeo

src/Utils/interface/stochastic_benchmark.jl

@@ -95,10 +95,22 @@ function generate_context(::AbstractStochasticBenchmark, rng, instance_sample::D
     return instance_sample
 end
 
+"""
+    objective_value(::ExogenousStochasticBenchmark, sample::DataSample, y, scenario) -> Real
+
+Compute the objective value of solution `y` for a given `scenario`.
+Must be implemented by each concrete [`ExogenousStochasticBenchmark`](@ref).
+
+This is the primary evaluation hook for stochastic benchmarks. The 2-arg fallback
+`objective_value(bench, sample, y)` dispatches here using the scenario stored in
+`sample.extra.scenario` (or averages over `sample.extra.scenarios`).
+"""
+function objective_value end
+
 """
     generate_anticipative_solver(::AbstractBenchmark) -> callable
 
-Return a callable that computes the anticipative (oracle) solution.
+**Optional.** Return a callable that computes the anticipative (oracle) solution.
 The calling convention differs by benchmark category:
 
 **Stochastic benchmarks** ([`AbstractStochasticBenchmark`](@ref)):
@@ -110,19 +122,9 @@ Returns `(env; reset_env=true, kwargs...) -> Vector{DataSample}`, a full traject
 `reset_env=true` resets the environment before solving (used for initial dataset building);
 `reset_env=false` starts from the current environment state (used inside DAgger rollouts).
 """
-function generate_anticipative_solver end
-
-"""
-    objective_value(::ExogenousStochasticBenchmark, sample::DataSample, y, scenario) -> Real
-
-Compute the objective value of solution `y` for a given `scenario`.
-Must be implemented by each concrete [`ExogenousStochasticBenchmark`](@ref).
-
-This is the primary evaluation hook for stochastic benchmarks. The 2-arg fallback
-`objective_value(bench, sample, y)` dispatches here using the scenario stored in
-`sample.extra.scenario` (or averages over `sample.extra.scenarios`).
-"""
-function objective_value end
+function generate_anticipative_solver(b::ExogenousStochasticBenchmark; kwargs...)
+    return error("generate_anticipative_solver is not implemented for $(typeof(b))")
+end
 
 """
     generate_parametric_anticipative_solver(::ExogenousStochasticBenchmark) -> callable
@@ -132,7 +134,11 @@ parametric anticipative subproblem:
 
     argmin_{y ∈ Y(instance)}  c(y, scenario) + θᵀy
 """
-function generate_parametric_anticipative_solver end
+function generate_parametric_anticipative_solver(b::ExogenousStochasticBenchmark; kwargs...)
+    return error(
+        "generate_parametric_anticipative_solver is not implemented for $(typeof(b))"
+    )
+end
 
 """
 $TYPEDSIGNATURES