Allocation

Overview

The Allocation model is responsible for taking a Region full of Cells, and a set of PotentialAgents, and re-allocating land to new agents. This can include mechanisms such as:

• replacing agents who have given up
• allowing new agents to force out existing ones
• some form of market
• top down optimisation
• etc.

The idea is to use the Competitiveness of Agents and PotentialAgents based on the supply, demand and ability to produce in the Region/Cell.

Note that allocation does not take place during the initial time step. The main reason is to allow CRAFTY to synchronise demand, calculate and synchronise supply, and determine competitiveness (which take place after allocation in the time step cycle). This leads to the assumption that initial land use patterns represent those of the initial time step.

Implementations

Current implementations are:

• SimpleAllocationModel: this looks for any empty cells, and puts the most competitive potential agent into each one in a random order
• GiveUpGiveInAllocationModel: in addition to the Simple model, this randomly samples potential agents based on their general competitiveness in the region(Region), and allows them to try to take over a number of cells.
• BestProductionFirstGiveUpGiveInAllocationModel: Cells that sampled potential agents seek to take over are selected based on the potential agents' potential production of its main service on the particular cell.
• InitiallyRandomAllocationModel: Allocates AFTs randomly, possibly based on set proportions of AFTs, during the time step after the initial step.

Caveats

Ownership changes

Land ownership within CRAFTY changes according to three different mechanisms, which simulate both individual and collective aspects of land use dynamics. Firstly, agents may abandon their land owing to their competitiveness score that falls below an agent’s giving-up threshold. Secondly, when land is unmanaged, due to abandonment or lack of managers, it can be taken over by a newly created agent, which is done for 20% of unmanaged cells each time step. By default, the set of functional roles is evaluated to determine their competitiveness score on each unmanaged cell (ca,i). The functional roles are sampled such that the probability of a role a attempting to take over a cell scales with its competitiveness on a cell with ‘perfect’ capital levels; 𝑃(𝑎) ∝ 𝑐􏰀,􏰁􏰐. For more general land use transitions, an allocation procedure runs between active and potential agents to determine ownership changes. This includes direct competition, where incoming agents attempt to take over existing 14 cells; such an attempt succeeds where the new agent has a competitiveness on the cell greater than or equal to the existing agent’s competitiveness plus its giving-in threshold: 𝑐􏰅􏰄􏰊 ≥ 𝑐􏰇􏰋􏰌􏰌 + 𝑔𝑖𝑣𝑖𝑛𝑔 􏰇􏰋􏰌􏰌.