% Energy behaviour change intervention model based on cognitive aspects: personal values, energy litarcy and persuasion model
% 15 April 2016

%Author: Nataliya Mogles, University of Bath


%In this version general energy mental model, or knowledge is included
%together with your own energy context awareness, or knowledge on the personal
%situation, your own context


clear all; 
close all;


% Simulation parameters
start_time  = 0;

end_time = 51;

delta_t = 1;

steps = (end_time - start_time) / delta_t;


%ALL model inputs and parameters have values on [0,1] scale


% Model parameters
% the sum of the weights of all variables contributing to/influencing another variable is always equal to 1

%Connection weights from the 4 environmental values to 'salient value'
%for a non-intervention scenario when no cue is presented
hedonic2value     = 1/4;
egoistic2value    = 1/4; 
altruistic2value  = 1/4;
biospheric2value  = 1/4;

%For the scenario when a value-based behaviour change intervention cue is
%presented, the connection weight from the framed value and 'salient value'
%is equal to primed2value and the other three value acquire weak2value conenction
primed2value = 0.9;
weak2value = 0.1/3;

%Connection weights from 'success expectancy', 'salient value' to 'motivation'
exp2motivation        = 1/2;
value2motivation      = 1/2; 

%Connection weights from 'barriers', 'energy literacy', 'context literacy' to 'ability'
barriers2ability      = 0.3;
literacy2ability      = 0.5;
context_literacy2ability = 0.2; %Situation awareness connection

%Connection weights from 'energy literacy', 'cue/trigger' to 'context information'
literacy2context = 0.8;
cue2context = 0.2;

%Connection weights from 'motivation', 'ability', 'cue/trigger' to 'behavioral intention'
motivation2behaviour    = 0.4;
ability2behaviour       = 0.4;
cue2behaviour           = 0.2;

%Parameters that define the speed of change of 'energy literacy'(eta) and success
%expectancy(eta_expect over time given the behaviour intervetnion cue/trigger is present 
gamma =0.01;
eta_expect = 0.005;
    
    
%CONCEPTS (VARIABLES)

%Initialisation of vectors for all model concepts (needed in MATLAB prior
%to the actual vairables initialisation
%these concepts are calculated on the fly

%4 environmental values
hedonic = zeros(end_time,1);
egoistic = zeros(end_time,1);
altruistic = zeros(end_time,1);
biospheric = zeros(end_time,1);


value = zeros(end_time,1); % salient value
expect = zeros(end_time,1); %success expectancy


barriers = zeros(end_time,1);
literacy = zeros(end_time,1); %energy literacy
context_literacy = zeros(end_time,1); %context information
educ = zeros(end_time,1); %educational component extracted from cue/trigger
cue_context = zeros(end_time,1);

motivation = zeros(end_time,1);
ability = zeros(end_time,1);  
behaviour = zeros(end_time,1);


%Actual initialisation of model concepts/vairables

%Numbers for environmental values (e.g. for this particular individual profile)
altruistic(1,1) = 0.5;
biospheric(1,1) = 0.5;
egoistic(1,1)= 0.8;
hedonic(1,1) = 0.8;

expect(1,1) = 0.5; %Initial success expectancy 

literacy(1,1) = 0.5; %Initial energy literacy

context_literacy(1,1) = 0; %context information

barriers(1,1) = 0.5;


 % Coding of different components of cue/trigger
 % position 1 - neutral energy info,  2 - hedonic value framing, 3 - egoistic value framing, 4 - biospheric value framing, 5 - altruisitc value framing, 6 - action prompt

 c = [1 0 0 0 0 0]; %neutral energy consumption cue - just knowledge without values activation
 c1 = [0 0 1 0 0 1]; % 3d element - egoistic value is framed
 c2 = [0 0 0 1 0 0]; %  4th element - biospheric value is framed
 
 c3 = [0 0 0 0 0 1]; %cue with only acions or no cue - the last 6th position in the cue vector defines the presence of action prompts
 c4 = [0 0 0 0 0 0]; %no cue
 
 
 % Cues are introduced during the 50 timesteps of a simulation: a vector of
 % 50 elements is created here; you can change cues and thus simulate
 % different types of interventions 
 cue = [c; c; c; c; c; c1; c1; c1; c1; c1; c1; c1; c1; c1; c1; c3; c3; c3; c3; c3; c3; c3; c3; c3; c3; c3; c3; c3; c3; c3; c2; c2; c2; c2; c2; c2; c2; c2; c2; c2; c2; c2; c4; c4; c4; c4; c4; c4; c4; c4; c4];   
 
                
 %MODEL SIMULATION
 
for i=1:(steps-1)
    
    %We assume that 4 values and barries are static during the whole simulation
    
    hedonic(i+1) = hedonic(i);
    egoistic(i+1) = egoistic(i);
    altruistic(i+1) = altruistic(i);
    biospheric(i+1) = biospheric(i);
    barriers(i+1) = barriers(i);
    
    
    % SALIENT VALUE
    if cue(i,2)==1
        value(i,1) = hedonic(i,1) * primed2value + egoistic(i,1) * weak2value  + biospheric(i,1) * weak2value  + altruistic(i,1) * weak2value;
    elseif cue(i,3)==1
        value(i,1) = hedonic(i,1) * weak2value + egoistic(i,1) * primed2value  + biospheric(i,1) * weak2value  + altruistic(i,1) * weak2value;
    elseif cue(i,4)==1
        value(i,1) = hedonic(i,1) * weak2value + egoistic(i,1) * weak2value  + biospheric(i,1) * primed2value  + altruistic(i,1) * weak2value;
    elseif cue(i,5)==1
        value(i,1) = hedonic(i,1) * weak2value + egoistic(i,1) * weak2value + biospheric(i,1) * weak2value + altruistic(i,1) * primed2value;
    else 
        value(i,1) = hedonic(i,1) * hedonic2value + egoistic(i,1) * egoistic2value  + biospheric(i,1) * biospheric2value  + altruistic(i,1) * altruistic2value;
    end
   
    % MOTIVATION 
    motivation(i) = expect(i) * exp2motivation + value(i) * value2motivation;
    
    if cue(i,1)==1
        educ(i) = 1;
    elseif cue(i,2)==1
        educ(i) = 1;
    elseif cue(i,3)==1
        educ(i) = 1;
    elseif cue(i,4)==1
        educ(i) = 1;
    elseif cue(i,5)==1
        educ(i) = 1;
    else 
        educ(i) = 0;
    end
    
    
    % ENERGY LITERACY  
    literacy(i+1) = literacy(i) + (gamma * educ(i)*(1-literacy(i)))* delta_t;
    
    
    %SUCCESS EXPECTANCY
     expect(i+1) = expect(i) + (eta_expect * educ(i)*(1-expect(i)))* delta_t;
    
   
    %CONTEXT LITERACY
    if cue(i,1)==1
        cue_context(i) = 1;
    elseif cue(i,2)==1
        cue_context(i) = 1;
    elseif cue(i,3)==1
        cue_context(i) = 1;
    elseif cue(i,4)==1
        cue_context(i) = 1;
    elseif cue(i,5)==1
        cue_context(i) = 1;
    else 
        cue_context(i) = 0;
    end
    
    context_literacy(i) = literacy(i) * literacy2context + cue_context(i) * cue2context;
    
       
    % ABILITY
    ability(i) = barriers(i) * barriers2ability + literacy(i) * literacy2ability + context_literacy(i) * context_literacy2ability; %ADD 2 more components: COGNITIVE SKILLS and context LITERACY 
    
    %BEHAVIOURAL INTENTION
    behaviour(i) = motivation(i) * motivation2behaviour + ability(i) * ability2behaviour + cue(i, 6) * cue2behaviour;

    
    %PLOT VARIABLES
    
    plot(behaviour, '-r');
    hold on;
    plot(motivation, '-m');
    hold on;
    plot(value, 'b');
    hold on;
    plot(cue(:,1), 'x-g');
    hold on;
    plot(cue(:,2), 'x-b');
    hold on;
    plot(cue(:,3), 'x-k');   
    hold on;
    plot(cue(:,4), 'x-c');
    hold on;
    plot(cue(:,5), 'x-y');
    hold on;
    
    hold off; 
    axis([0 50 0 1.2])
    xlabel('Time')
    ylabel('Model value')
    l1 = legend('behaviour','motivation', 'salient value', 'cue neutral', 'cue hedonic','cue egoistic', 'cue biospheris', 'cue altruistic');
    title('Cognitive Dynamics')
     
  
end