Medicines and medical devices are one of the most important parts a health service, so it is necessary to guarantee availability drugs for treatment that process can run effectively efficiently. The shortage medicines significant public problem, especially associated with life-threatening conditions. Meanwhile, inventory too large will increase investment funds risks such as loss, expiration da...

Poor ductility of titanium matrix composites with medium/high-strength reinforced carbonaceous nanomaterials (eg., graphene, carbon nanotubes etc.), has seriously restricted their wide-range engineering and practical industry utility. Herein, we propose a new methodology to significantly simultaneously enhance both tensile strength the composites. We ball milled Ti–6Al–4V (TC4) powders in-situ ...

We describe a model of utility-based agents that synthesizes information and determines the best way to make decisions in multi-agent systems. In this model, the beliefs are decomposed into two levels. The higher level represents the possible information about the possible worlds. The lower level subsequently estimates a number function for the belief. We also present a decision theory for this...

The increasing popularity of graph data in various domains has lead to a renewed interest in developing efficient graph matching techniques, especially for processing large graphs. In this paper, we study the problem of approximate graph matching in a large attributed graph. Given a large attributed graph and a query graph, we compute a subgraph of the large graph that best matches the query gr...

Utility theory and the principle of maximising the expected utility have, within the multi-agent community, had a great influence on multi-agent based decision. Even though this principle is often useful when evaluating a decision situation it is virtually impossible, except in very artificial situations, to use the more basic decision rules with its unrealistically strong requirements for the ...

We propose a new framework for multi-criteria optimization in constraint-based temporal reasoning. Motivated by a real-world domain, we augment one of the most expressive current formalisms, the Disjunctive Temporal Problem with Preferences (DTPP), in two crucial ways. First, we model optimality criteria as being attributed to subsets of soft constraints, in contrast to the direct mapping to in...

With the recent introduction of learning in integrated systems, there is a need to measure the utility of learned knowledge for these more complex systems. A diffiLulty arrises when there are multiple, possibly conflicting, utility metrics to be measured. In this paper, we present schemes which trade off conflicting utility metrics in order to achieve some global performance objectives. In part...

This paper proposes a game-theory based approach in a multi–target searching using a multi-robot system in a dynamic environment. It is assumed that a rough priori probability map of the targets’ distribution within the environment is given. To consider the interaction between the robots, a dynamic-programming equation is proposed to estimate the utility function for each robot. Based on this u...

in this paper, the optimal adaptive leader-follower consensus of linear continuous time multi-agent systems is considered. the error dynamics of each player depends on its neighbors’ information. detailed analysis of online optimal leader-follower consensus under known and unknown dynamics is presented. the introduced reinforcement learning-based algorithms learn online the approximate solution...