We introduce novel algorithms for generating random solutions from a uniform distribution over the solutions of a boolean satisfiability problem. Our algorithms operate in two pha...
We introduce an adversarial planning algorithm based on game tree search, which is applicable in large-scale multiplayer domains. In order to tackle the scalability issues of game...
We develop a hierarchical approach to planning for partially observable Markov decision processes (POMDPs) in which a policy is represented as a hierarchical finite-state control...
Enabling interactions of agent-teams and humans is a critical area of research, with encouraging progress in the past few years. However, previous work suffers from three key lim...
Nathan Schurr, Janusz Marecki, N. Kasinadhuni, Mil...
Distributed Constraint Optimization (DCOP) is a popular framework for cooperative multi-agent decision making. DCOP is NPhard, so an important line of work focuses on developing f...
Christopher Kiekintveld, Zhengyu Yin, Atul Kumar, ...