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Nowadays, Partially Observation Markov Decision Processes (POMDPs) provide a principled mathematical framework for solving some realistic problems with continuous spaces. The recently introduced Monte Carlo Value Iteration (MCVI) can tackle such problems with continuous state spaces. It uses a policy graph implicitly to represent the value function, instead of using a set of α-functions explicitly...
We consider a modular method to reinforcement learning that represents uncertainty of model parameters by maintaining probability distributions over them. The algorithm we call MBDP (model-based Bayesian dynamic programming) can be decomposed into two parallel types of inference: model learning and policy learning. During learning a model, we update posterior distributions of a model over observations...
Cloud Computing and Internet of Things are the buzzwords after Web 2.0. Cloud Computing, as a large-scale distributed computing paradigm, is a recent trend in IT that delivers applications as services over the Internet. The Internet of Things (IoT), as the future network of Internet, refers to a dynamic global network infrastructure in which physical and virtual “things” are seamlessly integrated...
The role of travel behavior of private cars in the vehicle routing schemes in city logistics distribution is investigated in this paper. A mixed logit model has been established to account for the influence of travel behavior to logistics distribution. A numerical study is conducted to understand the influence of the vehicle routing schemes in city logistics distribution.
Collaborative purchasing is a new type of purchasing methods, which not only can effectively integrate and control resources of small and middle sized enterprises (SMEs), but also can give full play to advantages of scale purchasing, reduce purchasing costs and streamline purchasing processes. Based on the analysis of the advantages of collaborative purchasing and the characteristics of multi-agent...
Grid resource management and scheduling are confronted with a great challenge. This paper presented a dynamic resource price-adjusting (RPA) strategy in computational Grid. Three new concepts and two new evaluation standards are defined. On the basis of these theories, a Grid resource scheduling algorithm based on marker-driven using dynamic RPA strategy is proposed. With the help of GridSim toolkit,...
Grids are positioned as systems which spread Internet environments with machines distributed across multiple organizations and administrative domains. Security has been the focus of the grid system recently. As an important part of security, trust in grid computing has been researched extensively. Based on subjective logic, a flexible trust model has been established to enhance the security of Grid...
Grid resource scheduling is one of the popular issues in grid computing research field. Ant colony algorithm (ACA) is an effective method to solve NP (non-deterministic polynomial) problems. By studying the process of resource scheduling in grid environment and ant colony algorithm for classic TSP problem, a strategy of resource scheduling based on ACA in grid environment was proposed. Then, the new...
Traditional contract net protocols can simply and flexibly solve the negotiation problem of multi-agent system (MAS). But they canpsilat work very well within the large scale system environment and is ineffective to solve the multi-issue negotiation problem. This paper investigates the reputation contract net protocol (RCNP) and proposes a novel contract net negotiation model based on RCNP. The model...
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