Exploring the Scope of Prognosis Agent Technology in Digital Manufacturing

It is an established fact that the last decade is evident for the advancement in manufacturing sector by the use of various digital manufacturing (DM) techniques. Agent technology has contributed far in the DM by simplifying and adding synergy to the various functionaries in form of static and mobile agents. The agents contribute in the paradigms of designing, diagnosis, production, marketing etc. In the international business market, the agent technology has increased the competence by providing fast, error free, customized services. The paper first reviews the work done in the field of applications of agent technology in digital manufacturing including the role of agent technology in prognosis and then the research object is to develop a framework for the prognosis of digital data feeded to the manufacturing facilities of DM system. The paper focus on the introduction and brief description of the manufacturing prognosis agent in context to Digital manufacturing. Key words: manufacturing prognosis agent, digital manufacturing, prognosis, agent technology, digital dat

Automated Vehicles are Expected to Increase Driving and Emissions Without Policy Intervention

Researchers at UC Davis explored what an automated vehicle future in the San Francisco Bay Area might look like by simulating:1) A 100% personal automated vehicle future and its effects on travel and greenhouse emissions.2) The introduction of an automated taxi service with plausible per-mile fares and its effects on conventional personal vehicle and transit travel.The researchers used the Metropolitan Transportation Commission’s activity-based travel demand model (MTC-ABM) and MATSim, an agent-based transportation model, to carry out the simulations. This policy brief summarizes the results, which provide insight into the relative benefits of each service and automated vehicle technology and the potential market for these services.View the NCST Project Webpag

Reagent removal of manganese from ground water

The study is aimed at the technology development of treating drinking water from ground waters with high manganese content and oxidizability. Current technologies, physical/chemical mechanisms and factors affecting in ground treatment efficiency are reviewed. Research has been conducted on manganese compound removal from ground waters with high manganese content (5 ppm) and oxidizability. The studies were carried out on granular sorbent industrial ODM-2F filters (0.7-1.5 mm fraction). It was determined that conventional reagent oxidization technologies followed by filtration do not allow us to obtain the manganese content below 0.1 ppm when treating ground waters with high oxidizability. The innovative oxidation-based manganese removal technology with continuous introduction of reaction catalytic agent is suggested. This technology is effective in alkalization up to pH 8.8-9. Potassium permanganate was used as a catalytic agent, sodium hypochlorite was an oxidizer and cauistic soda served an alkalifying agent. © Published under licence by IOP Publishing Ltd

A percolation model of eco-innovation diffusion: the relationship between diffusion, learning economies and subsidies

An obstacle to the widespread adoption of environmentally friendly energy technologies such as stationary and mobile fuel cells is their high upfront costs. While much lower prices seem to be attainable in the future due to learning curve cost reductions that increase rapidly with the scale of diffusion of the technology, there is a chicken and egg problem, even when some consumers may be willing to pay more for green technologies. Drawing on recent percolation models of diffusion by Solomon et al. [7], Frenken et al. [8] and Höhnisch et al. [9], we develop a network model of new technology diffusion that combines contagion among consumers with heterogeneity of agent characteristics. Agents adopt when the price falls below their random reservation price drawn from a lognormal distribution, but only when one of their neighbors has already adopted. Combining with a learning curve for the price as a function of the cumulative number of adopters, this may lead to delayed adoption for a certain range of initial conditions. Using agent-based simulations we explore when a limited subsidy policy can trigger diffusion that would otherwise not happen. The introduction of a subsidy policy seems to be highly effective for a given high initial price level only for learning economies in a certain range. Outside this range, the diffusion of a new technology either never takes off despite the subsidies, or the subsidies are unnecessary. Perhaps not coincidentally, this range seems to correspond to the values observed for many successful innovations.Innovation diffusion, learning economies, percolation, networks, heterogeneous agents, technology subsidies, environmental technologies

Select Suppliers from Electronic Markets with Incomplete Information

An agent want to buy products from e-market often encounters unknown suppliers, he then must choose between maximizing its expected utility according to the known suppliers and trying to learn more about the unknown suppliers, since this may improve its future rewards. This issue is known as the trade-off between exploitation and exploration. In this research, we study the problem of an agent how to select suppliers from electronic markets with incomplete information. The agent has no knowledge about suppliers, so he needs to learn the information by consuming their product and his object is to maximize total utility. We consider two different scenarios. The first is an agent selects a single supplier at each time period. By the introduction of Gittins index, we show that by using Gittins index technology, the agent can achieve the optimal solution. The second is an agent can select several suppliers at each time period, we propose four heuristic policies and evaluate them by building up a simulation tool

Coordination of supply chain activities: a coalition-based approach.

Companies operate in an environment increasingly demanding in terms of flexibility and reactivity. The introduction of the entities resulting from Distributed Artificial Intelligence (DAI) and Multi-Agent Systems (MAS) in the management of enterprises prove to be an interesting technology to simulate and reproduce the collaborative and adaptive behaviors of enterprises. This article models the coordination of the various collaborative parties both inside and outside a supply chain using coordination methods of MAS mainly coalition formation mechanisms. In this paper, we present our agent modeling of supply chains, and then we detail the coalition formation algorithm. Lastly, we illustrate our approach with an example chosen in the industrial domain.Distributed Artificial Intelligence (DAI); Multi-Agent System (MAS);

Protecting agents against malicious host attacks

The introduction of agent technology raises several security issues that are beyond conventional security mechanisms capability and considerations, but research in protecting the agent from malicious host attack is evolving. This research proposes two approaches to protecting an agent from being attacked by a malicious host. The first approach consists of an obfuscation algorithm that is able to protect the confidentiality of an agent and make it more difficult for a malicious host to spy on the agent. The algorithm uses multiple polynomial functions with multiple random inputs to convert an agent's critical data to a value that is meaningless to the malicious host. The effectiveness of the obfuscation algorithm is enhanced by addition of noise code. The second approach consists of a mechanism that is able to protect the integrity of the agent using state information, recorded during the agent execution process in a remote host environment, to detect a manipulation attack by a malicious host. Both approaches are implemented using a master-slave agent architecture that operates on a distributed migration pattern. Two sets of experimental test were conducted. The first set of experiments measures the migration and migration+computation overheads of the itinerary and distributed migration patterns. The second set of experiments is used to measure the security overhead of the proposed approaches. The protection of the agent is assessed by analysis of its effectiveness under known attacks. Finally, an agent-based application, known as Secure Flight Finder Agent-based System (SecureFAS) is developed, in order to prove the function of the proposed approaches

Explaining the Past with ABM: On Modelling Philosophy

This chapter discusses some of the conceptual issues surrounding the use of agent-based modelling in archaeology. Specifically, it addresses three questions: Why use agent-based simulation? Does specifically agent-based simulation imply a particular view of the world? How do we learn by simulating? First, however, it will be useful to provide a brief introduction to agent-based simulation and how it relates to archaeological simulation more generally. Some readers may prefer to return to this chapter after having read a more detailed account of an exemplar (Chap. 2) or of the technology (Chap. 3). Textbooks on agent-based modelling include Grimm and Railsback [(2005) Individual-based modeling and ecology, Princeton University Press, Princeton] and Railsback and Grimm [(2012) Agent-based and individual-based modeling: a practical introduction, Princeton University Press, Princeton], both aimed at ecologists, the rather briefer [Gilbert (2008) Agent-based models. Quantitative applications in the social sciences, Sage, Thousand Oaks, CA], aimed at sociologists, and [Ferber (1999) Multi-agent systems: an introduction to distributed artificial intelligence, English edn. Addison-Wesley, Harlow], which treats agent-based simulation from the perspective of artificial intelligence and computer science