Multi-agent planning problems with constraints on global resource consumption occur in several domains. Existing algorithms for solving Multi-agent Markov Decision Processes can compute policies that meet a resource constraint in expectation, but these policies provide no guarantees on the probability that a resource constraint violation will occur. We derive a method to bound constraint violat...

the aim of this paper is to present four strategies to increase the accuracy and speed of optimization of truss structures under the constraint of structural system failure probability (ssfp). in the first strategy based on the probability rules, a criterion is defined to avoid producing many correlated paths and obtain more accurate upper bound of ssfp. in the second strategy, the force method...

The main characteristic of any constraint solver is Constraint propagation. Then it is very important to be able to manage constraint propagation as efficiently as possible, we present a hybrid solver based on a Branch and Bound algorithm combined with constraint propagation to reduce the search space. Based on some observations of the solving process constraint propagation is triggered by some...

We introduce a constraint for one-dimensional bin packing. This constraint uses propagation rules incorporating knapsack-based reasoning, as well as a lower bound on the number of bins needed. We show that this constraint can significantly reduce search on bin packing problems. We also demonstrate that when coupled with a standard bin packing search strategy, our constraint can be a competitive...

The additive exponential noise channel with additive exponential interference (AENC-AEI) known non-causally at the transmitter is studied. This channel can be considered as an exponential version of the discrete memoryless channel with state known non-causally at the encoder considered by Gelfand and Pinsker. We make use of Gelf’and-Pinsker’s classic capacity Theorem to derive inner and outer b...

The handling of partially ordered degrees of preference can be important for constraint-based languages, especially when there is more than one criterion that we are interested in optimising. This paper describes branch and bound algorithms for a very general class of soft constraint optimisation problems. At each node of the search tree, a propagation mechanism is applied which generates an up...

Some n-ary constraints such as the alldiff constraints arise naturally in real fife constraint satisfaction problems (CSP). General purpose filtering algorithms could be applied to such constraints. By taking the semantics of the constraint into account, it is possible to design more efficient filtering algorithms. When the domains of the variables are totally ordered (e.g. all values are integ...

This paper proposes a novel algorithm for solving NP-hard constrained discrete minimization problems whose unconstrained versions are solvable in polynomial time such as constrained submodular function minimization. Applications of our algorithm include constrained MAP inference in Markov Random Fields, and energy minimization in various computer vision problems. Our algorithm assumes the exist...

When nominal interest rates are at the zero bound, so that monetary policy cannot be used to provide appropriate stymulus, tax policy can accomplish that at zero cost. There is no need to use ine¢ cient policies, such as wasteful public spending. This means that the zero bound on nominal interest rates is not a relevant constraint on both …scal and monetary policy. Key words : Zero Bound; Fisca...