The work herein continues the effort of achieving inter-cooperation between several Virtual Organisations (VOs) by utilising a heuristic genetic algorithm for resource discovery within such environments. The discovery process is based on an ad hoc strategy where each participant acts as an individual, detached from any centralized topologies articulated by VOs. The method is extended to an inter-collaborative model wherein discovery is derived from data extracted from a member snapshot profile. The primary challenging goal in building an ad hoc grid is supplying each grid member with specific directions for continuously maintaining information related to each community participant. Such information is stored at each VO member public profile and is available for advertising on the resource discovery process. The proposed approach will be able to define a collaborative model within a community domain and extend it to an intercommunication environment. To define these models it is essential to share a common understanding of the structure among community members. A way to achieve it is by utilizing Genetic Algorithms which offer a way to correlate VO members' roles and actions into a genetic chromosome of information and be able to be composed in a common format and be shared among VO participants. Consequently by mimicking the same processes that nature uses we deliver a case scenario of genetic algorithms in order to assist the resource discovery among inter-cooperated VOs.