On the crowdsourcing of behaviors for autonomous agents

Abstract

This paper is concerned with the problem of designing, from data, agents that are able to craft their behavior from a number of contributors in order to fulfill some agent-specific task. This is not necessarily known to the contributors. After formalizing this crowdsourcing process as a control problem, we present a result to synthesize behaviors from the information made available by the contributors. The result is turned into an algorithmic procedure and the theoretical findings are complemented via a numerical example.

Paper accepted on the IEEE Control Systems Letters

Cited by in corpus (2)

• Probabilistic design of optimal sequential decision-making algorithms in learning and control
• Discrete fully probabilistic design: towards a control pipeline for the synthesis of policies from examples