The mechanisms of emergence and evolution of cooperation — in populations of abstract individuals with diverse behavioral strategies in co-presence — have been undergoing mathematical study via Evolutionary Game Theory, inspired in part on Evolutionary Psychology. Their systematic study resorts as well to implementation and simulation techniques in parallel computers, thus enabling the study of aforesaid mechanisms under a variety of conditions, parameters, and alternative virtual games. The theoretical and experimental results have continually been surprising, rewarding and promising. Recently, in our own work we have initiated the introduction, in such groups of individuals, of cognitive abilities inspired on techniques and theories of Artificial Intelligence, namely those pertaining to Intention Recognition, encompassing the modeling and implementation of a tolerance/intolerance to errors in others — whether deliberate or not — and tolerance/intolerance to possible communication noise. As a result, both the emergence and stability of cooperation, in said groups of distinct abstract individuals, become reinforced comparatively to the absence of such cognitive abilities. The present paper aims to sensitize the reader to these Evolutionary Game Theory based studies and issues, which are accruing in importance for the modeling of minds with machines. And to draw attention to our own newly published results, for the first time introducing the use of Intention Recognition in this context, with impact on mutual tolerance.