986 resultados para Game world


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We investigate the effect of clusters in complex networks on efficiency dynamics by studying a simple efficiency model in two coupled small-world networks. It is shown that the critical network randomness corresponding to transition from a stagnant phase to a growing one decreases to zero as the connection strength of clusters increases. It is also shown for fixed randomness that the state of clusters transits from a stagnant phase to a growing one as the connection strength of clusters increases. This work can be useful for understanding the critical transition appearing in many dynamic processes on the cluster networks.

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Considering the fact, in the real world, that information is transmitted with a time delay, we study an evolutionary spatial prisoner's dilemma game where agents update strategies according to certain information that they have learned. In our study, the game dynamics are classified by the modes of information learning as well as game interaction, and four different combinations, i.e. the mean-field case, case I, case II and local case, are studied comparatively. It is found that the time delay in case II smoothes the phase transition from the absorbing states of C (or D) to their mixing state, and promotes cooperation for most parameter values. Our work provides insights into the temporal behavior of information and the memory of the system, and may be helpful in understanding the cooperative behavior induced by the time delay in social and biological systems.

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Serious concerns have been raised about the ecological effects of industrialized fishing1, 2, 3, spurring a United Nations resolution on restoring fisheries and marine ecosystems to healthy levels4. However, a prerequisite for restoration is a general understanding of the composition and abundance of unexploited fish communities, relative to contemporary ones. We constructed trajectories of community biomass and composition of large predatory fishes in four continental shelf and nine oceanic systems, using all available data from the beginning of exploitation. Industrialized fisheries typically reduced community biomass by 80% within 15 years of exploitation. Compensatory increases in fast-growing species were observed, but often reversed within a decade. Using a meta-analytic approach, we estimate that large predatory fish biomass today is only about 10% of pre-industrial levels. We conclude that declines of large predators in coastal regions5 have extended throughout the global ocean, with potentially serious consequences for ecosystems5, 6, 7. Our analysis suggests that management based on recent data alone may be misleading, and provides minimum estimates for unexploited communities, which could serve as the ‘missing baseline’8 needed for future restoration efforts.

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This paper describes a machine vision system that classifies reflectance properties of surfaces such as metal, plastic, or paper, under unknown real-world illumination. We demonstrate performance of our algorithm for surfaces of arbitrary geometry. Reflectance estimation under arbitrary omnidirectional illumination proves highly underconstrained. Our reflectance estimation algorithm succeeds by learning relationships between surface reflectance and certain statistics computed from an observed image, which depend on statistical regularities in the spatial structure of real-world illumination. Although the algorithm assumes known geometry, its statistical nature makes it robust to inaccurate geometry estimates.

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This thesis examines the problem of an autonomous agent learning a causal world model of its environment. Previous approaches to learning causal world models have concentrated on environments that are too "easy" (deterministic finite state machines) or too "hard" (containing much hidden state). We describe a new domain --- environments with manifest causal structure --- for learning. In such environments the agent has an abundance of perceptions of its environment. Specifically, it perceives almost all the relevant information it needs to understand the environment. Many environments of interest have manifest causal structure and we show that an agent can learn the manifest aspects of these environments quickly using straightforward learning techniques. We present a new algorithm to learn a rule-based causal world model from observations in the environment. The learning algorithm includes (1) a low level rule-learning algorithm that converges on a good set of specific rules, (2) a concept learning algorithm that learns concepts by finding completely correlated perceptions, and (3) an algorithm that learns general rules. In addition this thesis examines the problem of finding a good expert from a sequence of experts. Each expert has an "error rate"; we wish to find an expert with a low error rate. However, each expert's error rate and the distribution of error rates are unknown. A new expert-finding algorithm is presented and an upper bound on the expected error rate of the expert is derived.

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This report describes a knowledge-base system in which the information is stored in a network of small parallel processing elements ??de and link units ??ich are controlled by an external serial computer. This network is similar to the semantic network system of Quillian, but is much more tightly controlled. Such a network can perform certain critical deductions and searches very quickly; it avoids many of the problems of current systems, which must use complex heuristics to limit and guided their searches. It is argued (with examples) that the key operation in a knowledge-base system is the intersection of large explicit and semi-explicit sets. The parallel network system does this in a small, essentially constant number of cycles; a serial machine takes time proportional to the size of the sets, except in special cases.

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In this paper, we provide the text of an interview with Professor Michael Porter discussing his research and ideas relating to the microeconomic foundations of global competitiveness. The discussion provides a microeconomic perspective on some of the key issues relating to recent research on competitiveness, productivity, clusters, US economic leadership, economic growth and development.

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Tedd, L.A. (2003). The What? and How? of education and training for information professionals in a changing world: some experiences from Wales, Slovakia and the Asia-Pacific region. Journal of Information Science, 29(1), 79-86.

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Tedd, L.A. (2002). World Library Summit and visits to libraries in Singapore: a report. Program:electronic library and information systems, 36(4), 253-260.

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Falileyev, Alexander, in collaboration with Ashwin E. Gohil and Naomi Ward, Dictionary of Continental Celtic Place-Names: A Celtic Companion to the Barrington Atlas of the Greek and Roman World (CMCS Publications: Aberystwyth, 2010) Editor: Falileyev, Alexander in collaboration with Ashwin E. Gohil and Naomi Ward

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Egan, K., Barker, M. (2006). Rings around the World: Notes on the Challenges, Problems & Possibilities of International Audience Projects. Participations: Journal of Audience & Reception Studies, 3 (2). Sponsorship: This research was made possible by a grant from the Economic and Social Research Council (ESRC Grant No. 000-22-0323)

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G?l, Ayla. 'Iraq and world order: a Turkish perspective', in: 'The Iraq Crisis and World Order: Structural, Institutional and Normative Challenges', (Eds) Thakur, R., Sidhu, W. P. S., United Nations University Press, Hong Kong , pp.114-133, 2006 RAE2008

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Booth, Ken, Critical Security Studies and World Politics (Boulder, CO: Lynne Rienner Publishers, 2005), pp.ix+321 RAE2008

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Jackson, Peter, 'France and the Problems of Security and Disarmament after the First World War', Journal of Strategic Studies (2006) 29(2) pp.247-280 Special Issue: Enforcing arms limits: Germany post 1919; Iraq post 1991 RAE2008