Lack Of Perfect Knowledge Research Articles

The contribution of connected vehicles to network traffic control: A hierarchical approach

Connected vehicles (CVs) can considerably contribute to traffic control in the near future by providing real-time information. Such information can be exploited to identify the current traffic condition. However, challenges resulting from a high volume of data and lack of perfect knowledge in mixed traffic scenarios (consisting of CVs and conventional vehicles) have led to relatively sparse research in network-wide CV-based traffic control. To deal with such challenges, this paper proposes a hierarchical framework integrating three layers: (i) an intersection controller at individual intersections located in the center of the network, (ii) a network controller to regulate traffic coming into the network, and (iii) a phase controller to optimize the sequence of intersections’ signals. This approach permits the inclusion of information of (a limited number of) CVs to estimate and control queue lengths at individual intersections as well as the overall network load. Simulations carried out in VISSIM validate our approach in comparison with alternative control systems such as the application of (1) a traffic-responsive control, (2) a traffic accumulation regulator, or (3) a network signals coordinator. Moreover, comparisons between the proposed framework and a central system equipped with the information of all vehicles (giving rise to the optimal operation with, however, costly computation) under the consideration of different penetration rates of CVs and network layouts confirm that this framework results in competitive performance indicators, which, owing to the hierarchical structure, can be efficiently employed in real-time applications.

Control power as a special case of protean power: thoughts on Peter Katzenstein and Lucia Seybert'sProtean Power: Exploring the Uncertain and Unexpected in World Politics

AbstractHuman experience of control is an illusion; all forms of power are a special, transient, and unstable case of protean power. Taking risks is governed by critical uncertainty less because of our lack of perfect knowledge than because the world is physically and socially indeterminate. Power, thus, lies not only in agents' potential to dominate each other, but also in acting in concert to turn propensities into reality. Radical uncertainty is, therefore, not necessarily bad news. Whether protean power endangers or protects humanity depends less on calculating risks than on agents practicing common humanity values. I revise Katzenstein's and Seybert's concepts accordingly and illustrate by discussing Artificial Intelligence's challenges to humanity.

Sticky Belief Adjustment: A Double Hurdle Model and Experimental Evidence

Given a lack of perfect knowledge about the future, agents need to form expectations about variables affecting their decisions. We present an experiment where subjects sequentially receive signals about the true state of the world and need to form beliefs about which one is true, with payoffs related to reported beliefs. We control for risk aversion using the Offerman et al. (2009) technique. Against the baseline of Bayesian updating, we test for belief adjustment under-reaction and over-reaction and model the decision making process of the agent as a double hurdle model where agents first decide whether to adjust their beliefs and, if so, then decide by how much. We find evidence for sticky belief adjustment. This is due to a combination of: random belief adjustment; state-dependent belief adjustment, with many subjects requiring considerable evidence to change their beliefs; and Quasi-Bayesian belief adjustment, with insufficient belief adjustment when a belief change does occur.

Stochastic dynamics simulation with generalized interval probability

Two types of uncertainties are generally recognized in modelling and simulation, including variability caused by inherent randomness and incertitude due to the lack of perfect knowledge. In this paper, a generalized interval-probability theory is used to model both uncertainty components simultaneously, where epistemic uncertainty is quantified by generalized interval in addition to probability measure. Conditioning, independence, and Markovian probabilities are uniquely defined in generalized interval probability such that its probabilistic calculus resembles that in the classical probability theory. A path-integral approach can be taken to solve the interval Fokker–Planck equation for diffusion processes. A Krylov subspace projection method is proposed to solve the interval master equation for jump processes. Thus, the time evolution of both uncertainty components can be simulated simultaneously, which provides the lower and upper bound information of evolving probability distributions as an alternative to the traditional sensitivity analysis.

Role of hydrology and economics in water management policy under increasing uncertainty

Well-designed public policy stimulates social progress. However, when governments translate political vision into programmes for social change, the complexity of issues can overwhelm the policy-making process, creating disappointment and suboptimal outcomes. In this paper we examine why evidence-based policy-making approaches often fail to provide policy-makers with credible, consistent and clear outcomes matching broad social interest. The need for public policy primarily arises from a lack of perfect knowledge, which causes individuals and agencies to behave in ways that counter social interest. We therefore suggest that effective public policy formulation involves: determining what evidence is available, relevant and useful; as well as identifying critical gaps to making public policy necessary and meaningful. Murray-Darling Basin case examples highlight key stages in effective natural resource policy formulation, and sources of difficulties that need to be managed to maximize scientific contributions. These examples show that effective public policy decisions can still be made and information asymmetry managed via strong evidence, expert analysis to verify that evidence, and an understanding of knowledge gaps such that critical interventions can be agreed upon and objectives achieved in view of how they will be managed and resourced. Finally, we draw attention to the opportunities available and challenges that exist for hydrologists, economists and other social scientists to work together in assisting the policy process, and in particular to minimize the burden of information constraints in making effective water resource policy.

Second-order Monte Carlo uncertainty/variability analysis using correlated model parameters: application to salmonid embryo survival risk assessment

This paper presents a Monte Carlo uncertainty/variability analysis applied to assessment of salmonid embryo survival affected by the deposition of fine sand in the spawning gravel riverbed. For the system being modeled, the uncertainty originates from the lack of perfect knowledge about the spawning habitat, while the variability arises from the natural diversity in the amount of sand deposit. A second-order Monte Carlo simulation (MCS) procedure consisting of multiple realizations of model parameters and full-range iterations of input variable is used to separately propagate the knowledge uncertainty and natural variability of the system. Given that the three parameters of the present model are highly correlated (correlation coefficients >0.8), we use four multivariate methods (Iman–Conover method, standard normal transformation method, normal copula method, and maximum-entropy copula method) to generate correlated model parameters. The scatter plots of the correlated parameters generated with various methods demonstrate different correlation patterns. An important finding of the present uncertainty/variability analyses and risk assessments is that the outcomes resulting from the four correlated scenarios are very similar, regardless of the diverse correlation patterns. The output of the second-order MCS is a collection of cause–effect relations (spaghetti plot) that can facilitate the analyses of survival-rate uncertainty/variability. The favorable habitat conditions are also defined on the basis of the spaghetti plot. It is revealed that significant values of information are associated with the parameter correlations, especially when higher levels of embryo survival are targeted. The results further indicate that the outcomes of the independent (less realistic) scenario substantially differ from those of the correlated ones, indicating that the effect of parameter correlations should be incorporated into the MCS whenever possible. This work provides a useful paradigm for the systematic uncertainty/variability analyses in the context of ecological risk assessments.

Second-order Monte Carlo uncertainty/variability analysis using correlated model parameters: application to salmonid embryo survival risk assessment

This paper presents a Monte Carlo uncertainty/variability analysis applied to assessment of salmonid embryo survival affected by the deposition of fine sand in the spawning gravel riverbed. For the system being modeled, the uncertainty originates from the lack of perfect knowledge about the spawning habitat, while the variability arises from the natural diversity in the amount of sand deposit. A second-order Monte Carlo simulation (MCS) procedure consisting of multiple realizations of model parameters and full-range iterations of input variable is used to separately propagate the knowledge uncertainty and natural variability of the system. Given that the three parameters of the present model are highly correlated (correlation coefficients >0.8), we use four multivariate methods (Iman–Conover method, standard normal transformation method, normal copula method, and maximum-entropy copula method) to generate correlated model parameters. The scatter plots of the correlated parameters generated with various methods demonstrate different correlation patterns. An important finding of the present uncertainty/variability analyses and risk assessments is that the outcomes resulting from the four correlated scenarios are very similar, regardless of the diverse correlation patterns. The output of the second-order MCS is a collection of cause–effect relations (spaghetti plot) that can facilitate the analyses of survival-rate uncertainty/variability. The favorable habitat conditions are also defined on the basis of the spaghetti plot. It is revealed that significant values of information are associated with the parameter correlations, especially when higher levels of embryo survival are targeted. The results further indicate that the outcomes of the independent (less realistic) scenario substantially differ from those of the correlated ones, indicating that the effect of parameter correlations should be incorporated into the MCS whenever possible. This work provides a useful paradigm for the systematic uncertainty/variability analyses in the context of ecological risk assessments.

An introduction to second‐order random variables in human health risk assessments

Abstract When performing a human health risk assessment using probabilistic methods, risk assessors need a way to distinguish, analyze, and visualize both the variability and the uncertainty in a quantity. As described by many previous authors, first‐order random variables represent variability, i.e., the heterogeneity or diversity in a well‐characterized population which is usually not reducible through further measurement or study. Growing in popularity, second‐order random variables also include uncertainty, i.e., partial ignorance or lack of perfect knowledge about a poorly characterized phenomenon which may be reducible through further study. In this paper, we explore second‐order random variables as a way to encode and propagate variability and uncertainty separately.

Computation as Economics

We use computers to study economics, but few people realize that we can use economics to study and design computational systems. The reason is that computer networks can be regarded as a community of processes that in their interactions, strategies and lack of perfect knowledge, face the same issues as people in markets. This talk will describe how computers have evolved to a point where economics approaches are useful for designing them and understanding their dynamics. Examples will be given of existing computer systems that use market mechanisms and of novel phenomena that we uncovered when studying their evolution.

Distributed Computation as an Economic System

As computer networks grow and blanket the planet, they become a community of concurrent processes, which, in their interactions, strategies, and lack of perfect knowledge, become analogous to human market economies. Economics may thus offer new ways of designing and understanding the behavior of distributed computer systems.

Competition and Entrepreneurship

Kirzner, writing from a neo-Austrian economic perspective that is inherently dynamic with an emphasis on over time, offers a critique of the prevailing positivistic, value freedom of orthodox microeconomics and price theory, focusing on what he believes is its unrealistic emphasis on static equilibrium analysis. Kirzner criticizes the methodology of Robbinsian equililbrium analysis in which a competitive market is a situation in which buyers and sellers have perfect knowledge and in which decision-making is mechanical and its solutions given. This analysis, according to Kirzner, eliminates all consideration of the competitive process and of entrepreneurship (which is synonymous, for him, with competitive activity); the assumption of perfect knowledge is unrealistic. He offers a full elaboration of the Mises-Hayek view of entrepreneurship and competition as a process based on von Mises' idea of human action rather than Marshall's idea of economizing. Kirzner sees the entrepreneur as always alert to information and propelling the system forward by seeking out price discrepancies as opportunities for profit. This process depends not on impulses from technology or genius; rather every market participant is a potential entrepreneur who can exploit a situation, which depends on a lack of perfect knowledge among the market participants. Entrepreneurial activity is always competitive; and competitive activity is always entrepreneurial. Kirzner is thus also a critique of the Schumpeterian view of entrepreneurship as disrupter of equilibrium; rather the entrepreneur removes disequilibrium in a short-run movement to an equilibrium position. A Kirznerian entrepreneur is a decision-maker whose entire role arises from alertness to unnoticed opportunities or knowledge about market data. Within the context of entrepreneurial activity, he offers a neo-Austrian redefinition of the concept of monopoly and competition. Since for Kirzner entrepreneurship involves no element of resource ownership, monopoly is defined as the impact of input ownership on the competitive process, and not the shape of the demand curve facing a firm. A monopoly position can be won by an alert entrepreneur. In the light of his theory of competition, Kirzner provides a new theoretical place for advertising and selling costs. Advertising, which promotes and calls attention to product differentiation, is the weapon of competition, which allows competitive-entrepreneurial adjustments in the type of products placed in the market in disequilibrium. Kirzner's revaluation of advertising is thus opposed to the idea of advertising as a social waste. Kirzner also offers a new conception of economic welfare based on the coordination-of-knowledge-and-actions instead of the orthodox allocation of social resources standard. (TNM)

Economic Efficiency in Common Property Natural Resource Use: A Case Study of the Ocean Fishery

The Common property ocean fishery is often cited as an example of economic inefficiency in production. The usual recommendation is to restrict entry of fishermen so that incomes of those remaining are improved. Such logic would seem to indicate that the economic theory of common property natural resource use is not well developed. It was with this premise that the current investigation commenced. A mathematical model of productive interdependence among firms in a common pool situation was developed. Following this the concept of rising supply price for an industry exhibiting productive - interdependence was introduced. The concept of a fishing-day was introduced and it was argued that the firm viewed a fishing-day as one of its variable inputs. When the above concepts were combined with the biological model presented, a bioeconomic model of the fishery evolved. The model permitted illustration of the impact upon industry output from changes in: (1) technology; (2) demand for the product; and (3) fish population; and the chain of ramifications which result when current production is something other than the sustained yield of the fish stock. The usual charge that a common property fishery is inevitably overexploited was evaluated in the context of the bioeconomic model and seen to be false. The traditional recommendation to restrict entry such that fleet marginal cost equals fleet marginal revenue, so as to maximize rent, was shown, instead, to merely create higher - than-competitive returns (profit) for remaining fishermen. The disregard for those fishermen excluded by such action was questioned on equity grounds, as well as on grounds of economic efficiency. It was also demonstrated that depending upon demand for the product and technology of the industry, equating fleet marginal cost with fleet marginal revenue was not sufficient proof that the fish stock would not be overfished. The usual. concern for the welfare of the resource under common property exploitation was discussed and 'in light of present regulations, deemed to be of little moment in the fishery. A sole own9r could, perhaps, achieve7ecprl.omies of largescale production in the long run, but to do so would require access to a large number of fishing grounds. This being the case, extraction of monopoly profits would occur. Also to be weighed against possible gains from unified management would be the impact on those excluded from the fishery. Regard for regional employment, stability, and growth would seem to be ignored in the process of possibly reducing per unit production Costs in the fishery. The presence of productive .interdependence was seen to provide no basis for the charge that are present in a cornmon property fishery. A distinction between interdependence and exists which, up to now, has gone unrecognized. Thus, the recommendation for taxes to internalize the externalities was shown to be incorrect. Misallocation of fishing effort over grounds of different quality may exist, yet reallocation (costless) is more likely - to create differential profits for vessels on the better grounds, than it is in realizing social savings. The rudiments of resource allocLtion theory were presented, with particular reference to the fishery. It was concluded that the salvage value of commercial fishermen is lower than their acquisition cost and hence they .may be receiving their opportunity income. This being the case, the usual conclusion that society would benefit if excess fishermen produced other goods and services, appears weak. It was further hypothesized that, contrary to traditional thought, fishermen are more mobile than those occupational groups which stand to gain from long-term asset (land) appreciation. In conclusion, the presence of considerable uncertainty in a fishery, and the lack of perfect knowledge on the part of biologists and economists, renders the sweeping conclusions of traditional writers in fishery economics, and their subsequent policy recommendations, particularly vulnerable to incredulity.