/*! \page bdt_scenarios Use Case #1: Basic Scenarios of BDMToolbox A typical scenario may look like: \dot digraph estimation{ node [shape=box]; {rank="same"; "Data Source"; "Bayesian Model"} "Data Source" -> "Bayesian Model" [label="data"]; "Bayesian Model" -> "Result Logger" [label="estimation\n result"]; "Data Source" -> "Result Logger" [label="Simulated\n data"]; } \enddot Where active objects are: -# Data Sources (bdm::DS), providing access to various form of recursive data -# Bayesian estimators (bdm::BM), providing various exact and approximate algorithms for Bayesian inference -# Controllers (bdm::Controller), generating control strategies, both feedback, or feedforward -# Loggers (bdm::logger), for storing results of experiments These objects operate on data vectors, functions and probability densities: -# random variable (bdm::RV) is a name of a variable, used as named connectors in the scenarios, -# probability density functions, (bdm::pdf), both conditional and unconditional, -# functions, (bdm::fnc), of vector arguments, These classes act as "LEGO-like" bricks which can be composed a wide range of arrangements. 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 Lists of available objects are: - List of Data Sources - List of Conditional pdfs - List of Non-conditional pdfs - List of Loggers - List of Bayesian Models - List of Controllers For details of their use, see tutorials: - \ref userguide_pdf - \ref userguide_sim - \ref userguide_estim - \ref userguide_ctrl */