Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
Decentralized Markov Decision Processes are a powerful general model of decentralized, cooperative multi-agent problem solving. The high complexity of the general problem leads to...
A Complex Adaptive System (CAS) is a network of communicating, intelligent agents where each agent adapts its behavior in order to collaborate with other agents to achieve overall...
In this paper we lay the foundations for studying decisionmaking in complex dynamic construction management scenarios using situational simulations as experimental testbeds. We dr...
We study the notion of regret ratio proposed in [19] to deal with multi-criteria decision making in database systems. The regret minimization query proposed in [19] was shown to h...
Danupon Nanongkai, Ashwin Lall, Atish Das Sarma, K...