Classic direct mechanisms require full type (or utility) revelation from participating agents, something that can be very difficult in practical multi-attribute settings. In this...
Many learning tasks in adversarial domains tend to be highly dependent on the opponent. Predefined strategies optimized for play against a specific opponent are not likely to succ...
Achim Rettinger, Martin Zinkevich, Michael H. Bowl...
In this paper we describe an integrated multilevel learning approach to multiagent coalition formation in a real-time environment. In our domain, agents negotiate to form teams to...
In this paper, we present three parallel flexible approximate string matching methods on a parallel architecture with heterogeneous workstations to gain supercomputer power at lo...
Panagiotis D. Michailidis, Konstantinos G. Margari...
Scheduling of multiple parallel machinesin the face of sequence dependent setups and downstream considerations is a hard problem. No single efficient algorithm is guaranteedto pro...