Preparing complex jobs for crowdsourcing marketplaces requires careful attention to workflow design, the process of decomposing jobs into multiple tasks, which are solved by multi...
Learning from experimentation allows a system to acquire planning domain knowledge by correcting its knowledge when an action execution fails. Experiments are designed and planned...
This paper discusses the specifics of planning in multiagent environments. It presents the formal framework MAPL (“maple”) for describing multiagent planning domains. MAPL al...
Abstract— The Rapidly-exploring Random Tree (RRT) algorithm has found widespread use in the field of robot motion planning because it provides a single-shot, probabilistically c...
Matthew Zucker, James J. Kuffner, Michael S. Brani...
This paper presents an agent-based approach to assisting learners to dynamically adjust learning processes. The online learning process is first investigated where the importance ...