#include <ctime>
#include <climits>
#include <cmath>
#include <ros/ros.h>
#include "getgraph.h"
#include "algorithms.h"

Include dependency graph for algorithms.cpp:

Functions
bool	caminho_apartir_vizinhos_unicos (vertex vertex_web, int dimension, int caminho_principal, int &elem_max, int &custo_max, int seed)
bool	check_visited (vertex *vertex_web, int dimension)
void	clear_visited (vertex *vertex_web, uint dimension)
bool	computar_caminho_de_ida (vertex vertex_web, int dimension, int caminho_de_ida, int &elem_c_ida, int *caminho_principal, int elem_cp, int num_arcos)
int	computar_custo_caminho_final (vertex vertex_web, int caminho_final, int elem_caminho_final)
uint	conscientious_reactive (uint current_vertex, vertex vertex_web, double instantaneous_idleness)
int	count_intention (uint vertex, int *tab_intention, int nr_robots)
int	count_intention_cbls (uint vertex, int *tab_intention, int nr_robots, int id_robot)
void	create_source_and_dest_tables (vertex vertex_web, uint source, uint *destination, uint dimension)
int	cyclic (uint dimension, vertex vertex_web, int caminho_final)
int	devolve_viz_unicos (vertex *vertex_web, int vertice)
int	devolve_vizinhos_nao_visitados (vertex *vertex_web, int dimension, int vertice)
void	dijkstra (uint source, uint destination, int shortest_path, uint &elem_s_path, vertex vertex_web, uint dimension)
void	dijkstra_mcost (uint source, uint destination, int shortest_path, uint &elem_s_path, vertex vertex_web, double new_costs[][8], uint dimension)
double	get_edge_cost_between (vertex *vertex_web, uint vertex_A, uint vertex_B)
int	get_hist_idx (uint source, uint destination, uint source_vertex, uint dest_vertex, uint hist_dimension)
int	get_hist_idx_from_edge_cost (double *hist_sort, uint size, double edge_cost)
void	get_hist_sort (vertex vertex_web, double hist_sort, uint dimension)
int	get_max (uint *tab, uint tam_tab)
double	get_max_dbl (double *tab, uint tam_tab)
int	get_min (uint *tab, uint tam_tab)
double	get_min_dbl (double *tab, uint tam_tab)
uint	get_MSP_dimension (const char *msp_file)
void	get_MSP_route (uint route, uint dimension, const char msp_file)
uint	greedy_bayesian_strategy (uint current_vertex, vertex vertex_web, double instantaneous_idleness, double G1, double G2, double edge_min)
uint	heuristic_conscientious_reactive (uint current_vertex, vertex vertex_web, double instantaneous_idleness)
uint	heuristic_pathfinder_conscientious_cognitive (uint current_vertex, vertex vertex_web, double instantaneous_idleness, uint dimension, uint *path)
int	is_neigh (uint vertex1, uint vertex2, vertex *vertex_web, uint dimension)
int	learning_algorithm (uint current_vertex, vertex vertex_web, double instantaneous_idleness, double avg_idleness, int tab_intention, double histogram, uint source, uint destination, uint hist_dimension, int nr_robots, int id_robot, uint node_count, reinforcement_learning &RL)
void	load_real_histogram (double real_histogram, uint size_hist, char filename)
long double	log2 (const long double x)
int	longest_path (vertex vertex_web, int origem, int destino, int lista_v1v, int i_list, int dimension, int seed, int *caminho_parcial, int &elem_cp)
void	normalize_histogram (double real_histogram, double histogram, uint size_hist)
bool	pertence (int elemento, int *tab, int tam_tab)
int	pertence_idx (int elemento, int *tab, int tam_tab)
int	pertence_uint_idx (uint elemento, uint *tab, uint tam_tab)
bool	procurar_ciclo (vertex vertex_web, uint dimension, int caminho_principal, int &elem_caminho, int &custo_max, int seed)
uint	random (uint current_vertex, vertex *vertex_web)
void	shift_cyclic_path (uint start_vertex, int *caminho_final, int elem_caminho_final)
uint	state_exchange_bayesian_strategy (uint current_vertex, vertex vertex_web, double instantaneous_idleness, int *tab_intention, int nr_robots, double G1, double G2, double edge_min)
bool	UHC (vertex vertex_web, int v1, int caminho_principal, uint dimension)
void	update_likelihood (reinforcement_learning RL, double real_histogram, uint source, uint destination, uint hist_dimension, vertex vertex_web, int minimum_global_node_count, uint robotid)
void	update_likelihood_new (reinforcement_learning RL, uint node_count_table, double inst_idleness, uint dimension, double real_histogram, uint source, uint destination, uint hist_dimension, vertex vertex_web, uint robotid)
void	update_likelihood_old (reinforcement_learning RL, double real_histogram, double hist_sort, uint size_hist, vertex *vertex_web)
bool	verificar_arco_cp (int no_1, int no_2, int *caminho_principal, int elem_cp)
void	write_histogram_to_file (vertex vertex_web, double real_histogram, double histogram, uint source, uint *destination, uint hist_dimension, uint number, uint robotid)
void	write_reward_evolution (double reward, uint robotid)
Variables
uint	reward_count = 0

Function Documentation

bool caminho_apartir_vizinhos_unicos	(	vertex *	vertex_web,
		int	dimension,
		int *	caminho_principal,
		int &	elem_max,
		int &	custo_max,
		int	seed
	)

Definition at line 1638 of file algorithms.cpp.

bool check_visited	(	vertex *	vertex_web,
		int	dimension
	)

Definition at line 1736 of file algorithms.cpp.

void clear_visited	(	vertex *	vertex_web,
		uint	dimension
	)

Definition at line 929 of file algorithms.cpp.

bool computar_caminho_de_ida	(	vertex *	vertex_web,
		int	dimension,
		int *	caminho_de_ida,
		int &	elem_c_ida,
		int *	caminho_principal,
		int	elem_cp,
		int	num_arcos
	)

Definition at line 1778 of file algorithms.cpp.

int computar_custo_caminho_final	(	vertex *	vertex_web,
		int *	caminho_final,
		int	elem_caminho_final
	)

Definition at line 2248 of file algorithms.cpp.

uint conscientious_reactive	(	uint	current_vertex,
		vertex *	vertex_web,
		double *	instantaneous_idleness
	)

Definition at line 72 of file algorithms.cpp.

int count_intention	(	uint	vertex,
		int *	tab_intention,
		int	nr_robots
	)

Definition at line 301 of file algorithms.cpp.

int count_intention_cbls	(	uint	vertex,
		int *	tab_intention,
		int	nr_robots,
		int	id_robot
	)

Definition at line 313 of file algorithms.cpp.

void create_source_and_dest_tables	(	vertex *	vertex_web,
		uint *	source,
		uint *	destination,
		uint	dimension
	)

Definition at line 2643 of file algorithms.cpp.

int cyclic	(	uint	dimension,
		vertex *	vertex_web,
		int *	caminho_final
	)

Definition at line 2274 of file algorithms.cpp.

int devolve_viz_unicos	(	vertex *	vertex_web,
		int	vertice
	)

Definition at line 1310 of file algorithms.cpp.

int devolve_vizinhos_nao_visitados	(	vertex *	vertex_web,
		int	dimension,
		int	vertice
	)

Definition at line 1757 of file algorithms.cpp.

void dijkstra	(	uint	source,
		uint	destination,
		int *	shortest_path,
		uint &	elem_s_path,
		vertex *	vertex_web,
		uint	dimension
	)

Definition at line 415 of file algorithms.cpp.

void dijkstra_mcost	(	uint	source,
		uint	destination,
		int *	shortest_path,
		uint &	elem_s_path,
		vertex *	vertex_web,
		double	new_costs[][8],
		uint	dimension
	)

Definition at line 535 of file algorithms.cpp.

double get_edge_cost_between	(	vertex *	vertex_web,
		uint	vertex_A,
		uint	vertex_B
	)

Definition at line 2703 of file algorithms.cpp.

int get_hist_idx	(	uint *	source,
		uint *	destination,
		uint	source_vertex,
		uint	dest_vertex,
		uint	hist_dimension
	)

Definition at line 2691 of file algorithms.cpp.

int get_hist_idx_from_edge_cost	(	double *	hist_sort,
		uint	size,
		double	edge_cost
	)

Definition at line 2677 of file algorithms.cpp.

void get_hist_sort	(	vertex *	vertex_web,
		double *	hist_sort,
		uint	dimension
	)

Definition at line 2658 of file algorithms.cpp.

int get_max	(	uint *	tab,
		uint	tam_tab
	)

Definition at line 2799 of file algorithms.cpp.

double get_max_dbl	(	double *	tab,
		uint	tam_tab
	)

Definition at line 2812 of file algorithms.cpp.

int get_min	(	uint *	tab,
		uint	tam_tab
	)

Definition at line 2773 of file algorithms.cpp.

double get_min_dbl	(	double *	tab,
		uint	tam_tab
	)

Definition at line 2786 of file algorithms.cpp.

uint get_MSP_dimension ( const char * msp_file )

Definition at line 2596 of file algorithms.cpp.

void get_MSP_route	(	uint *	route,
		uint	dimension,
		const char *	msp_file
	)

Definition at line 2613 of file algorithms.cpp.

uint greedy_bayesian_strategy	(	uint	current_vertex,
		vertex *	vertex_web,
		double *	instantaneous_idleness,
		double	G1,
		double	G2,
		double	edge_min
	)

Definition at line 226 of file algorithms.cpp.

uint heuristic_conscientious_reactive	(	uint	current_vertex,
		vertex *	vertex_web,
		double *	instantaneous_idleness
	)

Definition at line 124 of file algorithms.cpp.

uint heuristic_pathfinder_conscientious_cognitive	(	uint	current_vertex,
		vertex *	vertex_web,
		double *	instantaneous_idleness,
		uint	dimension,
		uint *	path
	)

Definition at line 642 of file algorithms.cpp.

int is_neigh	(	uint	vertex1,
		uint	vertex2,
		vertex *	vertex_web,
		uint	dimension
	)

Definition at line 522 of file algorithms.cpp.

int learning_algorithm	(	uint	current_vertex,
		vertex *	vertex_web,
		double *	instantaneous_idleness,
		double *	avg_idleness,
		int *	tab_intention,
		double *	histogram,
		uint *	source,
		uint *	destination,
		uint	hist_dimension,
		int	nr_robots,
		int	id_robot,
		uint *	node_count,
		reinforcement_learning &	RL
	)

IMMEDIATE LOCAL NORMALIZED PRIOR - BEFORE

LOCAL LOOKAHEAD PRIOR

IMMEDIATE LOCAL NORMALIZED PRIOR - BEFORE

LOCAL LOOKAHEAD PRIOR

CALCULATE DECISION ENTROPY

NORMALIZE ENTROPY ACCORDING TO NR# DECISIONS

Definition at line 3445 of file algorithms.cpp.

void load_real_histogram	(	double *	real_histogram,
		uint	size_hist,
		char *	filename
	)

Definition at line 2716 of file algorithms.cpp.

long double log2 ( const long double x ) [inline]

Definition at line 53 of file algorithms.cpp.

int longest_path	(	vertex *	vertex_web,
		int	origem,
		int	destino,
		int *	lista_v1v,
		int	i_list,
		int	dimension,
		int	seed,
		int *	caminho_parcial,
		int &	elem_cp
	)

Definition at line 1321 of file algorithms.cpp.

void normalize_histogram	(	double *	real_histogram,
		double *	histogram,
		uint	size_hist
	)

Definition at line 2745 of file algorithms.cpp.

bool pertence	(	int	elemento,
		int *	tab,
		int	tam_tab
	)

Definition at line 832 of file algorithms.cpp.

int pertence_idx	(	int	elemento,
		int *	tab,
		int	tam_tab
	)

Definition at line 845 of file algorithms.cpp.

int pertence_uint_idx	(	uint	elemento,
		uint *	tab,
		uint	tam_tab
	)

Definition at line 2760 of file algorithms.cpp.

bool procurar_ciclo	(	vertex *	vertex_web,
		uint	dimension,
		int *	caminho_principal,
		int &	elem_caminho,
		int &	custo_max,
		int	seed
	)

Definition at line 942 of file algorithms.cpp.

uint random	(	uint	current_vertex,
		vertex *	vertex_web
	)

Definition at line 58 of file algorithms.cpp.

void shift_cyclic_path	(	uint	start_vertex,
		int *	caminho_final,
		int	elem_caminho_final
	)

Definition at line 2564 of file algorithms.cpp.

uint state_exchange_bayesian_strategy	(	uint	current_vertex,
		vertex *	vertex_web,
		double *	instantaneous_idleness,
		int *	tab_intention,
		int	nr_robots,
		double	G1,
		double	G2,
		double	edge_min
	)

Definition at line 325 of file algorithms.cpp.

bool UHC	(	vertex *	vertex_web,
		int	v1,
		int *	caminho_principal,
		uint	dimension
	)

Definition at line 858 of file algorithms.cpp.

void update_likelihood	(	reinforcement_learning	RL,
		double *	real_histogram,
		uint *	source,
		uint *	destination,
		uint	hist_dimension,
		vertex *	vertex_web,
		int	minimum_global_node_count,
		uint	robotid
	)

node counts normalizados pelo vertex degree*2 (se deg>1)

reward se for a menor node_cont (não normalizado) do grafo global

Dimension this as a parameter (alfa) in the reward funcion

alfa = 100

1- CALCULAR A NOVA Idleness BASEADA NO INSTANTE DE TEMPO ***

2- Quanto mais baixa a entropia, maior o reward ou punishment

ALTERADO PARA SER EDGE DIRIGIDA: Faz mais sentido...

Definition at line 2977 of file algorithms.cpp.

void update_likelihood_new	(	reinforcement_learning	RL,
		uint *	node_count_table,
		double *	inst_idleness,
		uint	dimension,
		double *	real_histogram,
		uint *	source,
		uint *	destination,
		uint	hist_dimension,
		vertex *	vertex_web,
		uint	robotid
	)

AQUI POSSO PENALIZAR BASTANTE = NÓ QUE ACABEI DE VISITAR E NAO QUERO CA VOLTAR

reward se for a menor node_cont (não normalizado) do grafo global

Definition at line 3206 of file algorithms.cpp.

void update_likelihood_old	(	reinforcement_learning	RL,
		double *	real_histogram,
		double *	hist_sort,
		uint	size_hist,
		vertex *	vertex_web
	)

1- CALCULAR A NOVA Idleness BASEADA NO INSTANTE DE TEMPO ***

2- Quanto mais baixa a entropia, maior o reward ou punishment

Definition at line 2872 of file algorithms.cpp.

bool verificar_arco_cp	(	int	no_1,
		int	no_2,
		int *	caminho_principal,
		int	elem_cp
	)

Definition at line 1710 of file algorithms.cpp.

void write_histogram_to_file	(	vertex *	vertex_web,
		double *	real_histogram,
		double *	histogram,
		uint *	source,
		uint *	destination,
		uint	hist_dimension,
		uint	number,
		uint	robotid
	)

Definition at line 2825 of file algorithms.cpp.

void write_reward_evolution	(	double	reward,
		uint	robotid
	)

Definition at line 2853 of file algorithms.cpp.

Variable Documentation

uint reward_count = 0

Definition at line 47 of file algorithms.cpp.

Functions

Variables

Function Documentation

Variable Documentation