Construct version 5.4.3
An agent based modeling framework
graph_names Namespace Reference

Names of all graphs/networks used in Construct's model library More...

Variables

const std::string active = "agent active time network"
 
const std::string current_loc = "agent current location network"
 
const std::string group_beliefs = "agent group belief network"
 
const std::string group_knowledge = "agent group knowledge network"
 
const std::string agent_groups = "agent group membership network"
 
const std::string init_count = "agent initiation count network"
 
const std::string loc_learning_rate = "agent location learning rate network"
 
const std::string loc_preference = "agent location preference network"
 
const std::string mail_usage = "agent mail usage by medium network"
 
const std::string recep_count = "agent reception count network"
 
const std::string agent_trust = "agent trust network"
 
const std::string b_k_wgt = "belief knowledge weight network"
 
const std::string belief_msg_complex = "belief message complexity network"
 
const std::string beliefs = "belief network"
 
const std::string b_sim_wgt = "belief similarity weight network"
 
const std::string btm = "belief transactive memory network"
 
const std::string comm_access = "communication medium access network"
 
const std::string comm_pref = "communication medium preferences network"
 
const std::string fb_friend = "facebook friend network"
 
const std::string emotion_net = "emotion network"
 
const std::string emot_broad_bias = "emotion broadcast bias network"
 
const std::string emot_broad_first = "emotion broadcast first order network"
 
const std::string emot_broad_second = "emotion broadcast second order network"
 
const std::string emot_read_first = "emotion reading first order network"
 
const std::string emot_read_second = "emotion reading second order network"
 
const std::string emot_reg_bias = "emotion regulation bias network"
 
const std::string emot_reg_first = "emotion regulation first order network"
 
const std::string emot_reg_second = "emotion regulation second order network"
 
const std::string interact_k_wgt = "interaction knowledge weight network"
 
const std::string interact = "interaction network"
 
const std::string interact_prob = "interaction probability network"
 
const std::string soi = "interaction sphere network"
 
const std::string k_exp_wgt = "knowledge expertise weight network"
 
const std::string k_forget_prob = "knowledge forgetting prob network"
 
const std::string k_forget_rate = "knowledge forgetting rate network"
 
const std::string k_diff = "knowledge learning difficulty network"
 
const std::string k_msg_complex = "knowledge message complexity network"
 
const std::string knowledge = "knowledge network"
 
const std::string k_priority = "knowledge priority network"
 
const std::string k_sim_wgt = "knowledge similarity weight network"
 
const std::string k_strength = "knowledge strength network"
 
const std::string ktm = "knowledge transactive memory network"
 
const std::string k_trust = "knowledge trust network"
 
const std::string ktrust_resist = "knowledge trust resistance network"
 
const std::string learnable_k = "learnable knowledge network"
 
const std::string loc_knowledge = "location knowledge network"
 
const std::string loc_learning_limit = "location learning limit network"
 
const std::string loc_medium_access = "location medium access network"
 
const std::string location_network = "location network"
 
const std::string mail_check_prob = "mail check probability network"
 
const std::string medium_k_access = "medium knowledge access network"
 
const std::string kttm = "knowledge trust transactive memory network"
 
const std::string phys_prox = "physical proximity network"
 
const std::string phys_prox_wgt = "physical proximity weight network"
 
const std::string propensity = "public propensity network"
 
const std::string subreddit_mem = "subreddit membership network"
 
const std::string soc_prox = "social proximity network"
 
const std::string soc_prox_wgt = "social proximity weight network"
 
const std::string dem_prox = "sociodemographic proximity network"
 
const std::string dem_prox_wgt = "sociodemographic proximity weight network"
 
const std::string subs = "subscription network"
 
const std::string sub_probability = "subscription probability network"
 
const std::string target_info = "target information network"
 
const std::string task_assignment = "task assignment network"
 
const std::string task_availability = "task availability network"
 
const std::string task_completion = "task completion network"
 
const std::string task_guess_prob = "task guess probability network"
 
const std::string task_k_importance = "task knowledge importance network"
 
const std::string task_k_req = "task knowledge requirement network"
 
const std::string btm_msg_complex = "transactive belief message complexity network"
 
const std::string ktm_msg_complex = "transactive knowledge message complexity network"
 
const std::string twit_follow = "twitter follower network"
 
const std::string unused = "unused knowledge network"
 
const std::string banned_user = "banned user network"
 
const std::string k_type = "knowledge type network"
 

Detailed Description

Names of all graphs/networks used in Construct's model library