Many scheduling problems reside in uncertain and dynamic environments – tasks have a nonzero probability of failure and may need to be rescheduled. In these cases, an optimized ...
Andrew M. Sutton, Adele E. Howe, L. Darrell Whitle...
The objective of this paper is to study the existing methods for unsupervised object recognition and image categorization and propose a model that can learn directly from the outp...
We consider the problem of finding an n-agent jointpolicy for the optimal finite-horizon control of a decentralized Pomdp (Dec-Pomdp). This is a problem of very high complexity ...
In several applications of logic programming and Transaction Logic, such as, planning, trust management and independent Semantic Web Services, an action might produce incomplete f...
In sequential decision-making problems formulated as Markov decision processes, state-value function approximation using domain features is a critical technique for scaling up the...