A GENERAL TECHNIQUE FOR COMPUTING EVOLUTIONARILY STABLE STRATEGIES BASED ON ERRORS IN DECISION-MAKING

Realistic models of contests between animals will often involve a seri es of state-dependent decisions by the contestants. Computation of evo lutionarily stable strategies for such state-dependent dynamic games a re usually based on damped iterations of the best response map. Typica lly this map is discontinuous so that iterations may not converge and even if they do converge it may not be clear if the limiting strategy is a Nash equilibrium. We present a general computational technique ba sed on errors in decision making that removes these computational diff iculties. We show that the computational technique works for a simple example (the Hawk-Dove game) where an analytic solution is known, and prove general results about the technique for more complex games. It i s also argued that there is biological justification for inclusion of the types of errors we have introduced. (C) 1997 Academic Press Limite d.