I am trying to determine an objective way for a self-interested agent to calculate the optimal buying/selling price for goods in a multi-agent simulation not dissimilar to Sugarscape (http://en.wikipedia.org/wiki/Sugarscape). The simulation is as follows:Each agent has a stock of food F, a stock of money G, a certain amount of energy, E, and a position (x, y) on a square grid. Moving from one square to a neighboring square expends A units of energy, and energy is naturally expended at a rate of B units per simulation day. An agent has the following options available to it during each day: consume a unit of food to increase its energy by Q units; move to another location (provided it has sufficient energy), forage for food (expend P units of energy to obtain a [possibly unknown] quantity of food), or trade with a neighboring agent for a mutually-agreeable price.Each agent's goal is to maximize its utility function U(E, F, G) without regard for that of other agents.Right away, this seems to give a base use value of food: Vuse = U(E + Q, F - 1, G) - U(E, F, G), but if this was the whole story, this wouldn't be an interesting problem.It seems the most general (but exponential-time) solution would look something like this:Function SearchActions(State S):    Add(consume food) to action set    Add(forage for food) to action set    For each other agent A        For each possible trading price P            Add(trade with A at price P) to action set    For each action X in action set        S' = Apply X to S        SearchActions(S')    Return optimal XEnd functionHowever, the major difficulty gets swept under the rug by for each possible price, because the price that agent A will buy/sell for is itself dependent on an identical calculation...e.g. My calculation of the value depends on either what I can get from using it myself, or what someone else will pay for it...but what they will pay for it depends on what I will pay for it.How do you cut this knot?I know this problem has been solved before...but I cannot find any references to it, let alone any actual implementations. The closest I've come has been a paper about Strategic Planning in SugarScape, but it only seems to give the results of the planning, rather than explaining how the planning is done.
Determinining value in multi-agent microeconomical simulation
planning;artificial intelligence;search;simulation;economics