Model Decision-Making

Ok, so following on from the 'model dilemma' post, I have decided, rather than choosing between the two separate movement decision options, to combine them together.

So, instead of having my agents move around looking for food and ignoring the type of habitat, they now make a decision based on 4 factors:

1. amount of food
2. habitat cost
3. pheromone cost
4. road cost

Decisions are now based on a weighting of these 4 parameters, with the need to move still driven by food requirements, but the decision inherently based on weighing up pros of food availability vs the cons of habitat/pheromone/road cost (which implicitly include a range of other factors that may be important to movement decision making by jaguars).

A total 'cell quality' value now exists for each neighbour and the jaguar choose the cell with the best cell quality, calculated as follows:

cellQuality = food - (0.1*habitatCost) - (0.1*pheromoneCost) - roadCost

Food is explicitly linked to habitat, with the food reaching a maximum of 10 in good quality preferential forest habitats.

habitatCost and pheromoneCost reach a maximum level of 100 and so are multiplied by 0.1 to standardise the relative values to that of food. 

roadCost is a tricky one, I haven't yet decided whether to go to a maximum cost of 10 here or to 100, to provide a better relative difference between road types..... The main tricky aspect here is that I want to encourage males to use the trails (classed as a type of road) but discourage the females from doing the same. In this way, males view the smaller forest trails as either of no cost or negative cost (TBC) whereas females see them of some low cost value.

This method of combining the food and cost decision making loops takes out around 3/4 of the steps required in the food loop, making only one additional step to the cost loop - a biased choice towards maximising food if the jaguar has low food reserves. 

Adding in different costs for the trails also provides some inherent decision making towards using trails or not, versus the hard-coding probabilistic choice to avoid or prefer trails that was used in both the food and cost loops.