Record linkage analysis, which matches records referring to the same real world entities from different data sets, is an important task in data integration. Uncertainty often exi...
Planning under uncertainty is an important and challenging problem in multiagent systems. Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful fr...
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
Computer agents participate in many collaborative and competitive multiagent domains in which humans make decisions. For computer agents to interact successfully with people in su...
We describe the spatial Agent-Based Computational Laboratory that we have developed to study the pandemic influenza risks of US cities. This research presented a series of interes...