Abstract. In this paper we compare state-of-the-art multi-agent reinforcement learning algorithms in a wide variety of games. We consider two types of algorithms: value iteration a...
H. Jaap van den Herik, Daniel Hennes, Michael Kais...
Multiagent resource allocation is a timely and exciting area of research at the interface of Computer Science and Economics. One of the main challenges in this area is the high co...
Decentralized POMDPs provide an expressive framework for sequential multi-agent decision making. Despite their high complexity, there has been significant progress in scaling up e...
This paper presents SAgent, a general-purpose mobile agent security framework that is designed to protect the computations of mobile agent applications in potentially hostile envi...
Members of high-performing human teams can often anticipate information needs of teammates and offer relevant information to them proactively. Such capabilities are highly desirab...