/*!
\page bdt_scenarios Basic Scenarios of BDMToolbox

The basic elements of BDM are:
 -# probability density functions, (bdm::pdf), both conditional and unconditional 
 -# functions, (bdm::fnc), of vector arguments
 -# Bayesian estimators (bdm::BM), providing variaous exact and approximate algorithms for Bayesian inference
 -# Data Sources (bdm::DS), providing access to various form of recursive data
 -# Controllers (bdm::Controller), generating control strategies, both feedback, or feedforward
 -# Loggers (bdm::logger), for storing results of experiments

The objects are designed to allow mutual combination of these. Distinction of what needs to be connected where is provided by class RV which stands for random variable.

Predefined scenarios implemented in mex are:

 - Simulation, see \ref simulator.cpp
 - Estimation, see \ref estimator.cpp
 - Controll Loop, see \ref controlloop.cpp
 - Multiple-Participant Decision-Making, see \ref arena.cpp

For details of their use, see tutorials:
 - \ref userguide_pdf
 - \ref userguide_sim
 - \ref userguide_estim
 - \ref userguide_ctrl
 
 

 */
