Traffic measurement is a critical component for the control and engineering of communication networks. We argue that traffic measurement should make it possible to obtain the spati...
Many current state-of-the-art planners rely on forward heuristic search. The success of such search typically depends on heuristic distance-to-the-goal estimates derived from the ...
Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
This paper discusses the specifics of planning in multiagent environments. It presents the formal framework MAPL (“maple”) for describing multiagent planning domains. MAPL al...
Recent work has applied game-theoretic models to real-world security problems at the Los Angeles International Airport (LAX) and Federal Air Marshals Service (FAMS). The analysis o...
Christopher Kiekintveld, Milind Tambe, Janusz Mare...