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Efficient Complex Tasks Allocation within Agents Environment of Known Capabilities

In this paper we analyze and propose solutions for complex tasks allocation problem that have predetermined and known overall payments for any given task. More specifically, here we concentrated on scenarios where agents are willing to undertake any subtask of their capabilities but can strategize on their cost reported for completing this subtask. For this environment we proved that no individually rational and budget balanced protocol can exist which archives an efficient solution. Moreover, there are settings in this environment for which such protocols exist, but they are again setting specific. Given this we then go onto develop protocol for important class of settings, that we prove to be budget balanced, individually rational and is incentive compatible in Bayesian Nash equilibrium. Moreover, although it does not achieve the efficient allocation solution, we show by experiments that for the majority of cases a near optimal (above 95%) solution is achieved.