The problem of allocating tasks to workers is of long standing fundamental importance. Examples of this include the classical problem of assigning computing tasks to nodes in a distributed computing environment, as well as the more recent problem of crowdsourcing where a broad array of tasks are slated to be completed by human workers. Extensive research into this problem generally addresses im...

Task allocation is a classic distributed problem in which a set of p potentially faulty processes must cooperate to perform a set of m tasks. This paper considers a new dynamic version of the problem, in which tasks are injected adversarially during an asynchronous execution. We give the first asynchronous shared-memory algorithm for dynamic task allocation, and we prove that our solution is op...

Existing task allocation methods broadcast a request when they do not know who to ask for a certain task. In many situations this is not a good idea, either because of the burden on all other agents, or because not everyone can be trusted with the information that this task is requested. When considering coalitions, existing methods try all combinations, but sometimes need to limit the maximum ...

We study dynamic task allocation when providers' expertise evolves endogenously through training. characterize optimal assignment protocols and compare them to discretionary procedures, where it is the clients who select their service providers. Our results indicate that welfare gains from centralization are greater tasks arrive more rapidly, training technologies improve. Monitoring seniors' b...