We consider the situation where a group of agents is involved in the achievement of a common goal. Each agent owns a set of actions that are partial solutions for the problem to be solved. Different agents may have the same actions. In order to decide which action to select from the various agents, actions are assessed using a set of attributes. These attributes measure the extent to which the actions satisfy the common objective. The problem of action selection becomes more complex if we consider that agents do not necessarily know each oth-ers' actions, which complicates the coordination of joint actions. Interactions between agents may be affected by antagonistic personal interests. The more actions are selected from an agent, the greater his/her budget. Based on a Multiple Criteria Decision Analysis (MCDA) framework and a fuzzy model that links actions to the satisfaction of objectives , this paper examines the problem of collective selection of the necessary actions to achieve a goal. Only information necessary for the progress of the collective action is shared, and collective and personal goals coexist and are to be taken into account.