Partially Observable Markov Decision Process (POMDP) is a popular framework for planning under uncertainty in partially observable domains. Yet, the POMDP model is riskneutral in ...
In this paper, we study a service procurement problem with uncertainty as to whether service providers are capable of completing a given task within a specified deadline. This typ...
Enrico Gerding, Sebastian Stein, Kate Larson, Alex...
We explore settings where a principal must make a decision about which action to take to achieve a desired outcome. The principal elicits the probability of achieving the outcome ...
Many problems in AI and multi-agent systems research are most naturally formulated in terms of the abilities of a coalition of agents. There exist several excellent logical tools ...
Natasha Alechina, Brian Logan, Nguyen Hoang Nga, A...
The static asset protection problem (SAP) in a road network is that of allocating resources to protect vertices, given any possible behavior by an adversary determined to attack t...
John P. Dickerson, Gerardo I. Simari, V. S. Subrah...
A major research challenge in multi-agent systems is the problem of partitioning a set of agents into mutually disjoint coalitions, such that the overall performance of the system...
Tomasz P. Michalak, Jacek Sroka, Talal Rahwan, Mic...
DPOP is an algorithm for distributed constraint optimization which has, as main drawback, the exponential size of some of its messages. Recently, some algorithms for distributed c...