While the class of congestion games has been thoroughly studied in the multi-agent systems literature, settings with incomplete information have received relatively little attenti...
In several agent-oriented scenarios in the real world, an autonomous agent that is situated in an unknown environment must learn through a process of trial and error to take actio...
Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...
This paper argues that the agent-based simulation approach is just the one appropriate to the social sciences (including economics). Although there were many predecessor approache...
The most important and interesting of the computing challenges we are facing are those that involve the problems and opportunities afforded by massive decentralization and disinte...