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.

arXiv commentPaper accepted on the IEEE Control Systems Letters

References in corpus (2)

• Distributed Ledger Technology, Cyber-Physical Systems, and Social Compliance
• Data-Driven LQR Control Design

Cited by in corpus (4)

• On a probabilistic approach to synthesize control policies from example datasets
• Probabilistic design of optimal sequential decision-making algorithms in learning and control
• On the design of autonomous agents from multiple data sources
• Discrete fully probabilistic design: towards a control pipeline for the synthesis of policies from examples