Mathematical models are often used in system identification applications. The dynamics of most systems, however, change over time and the sources of these changes cannot always be directly determined or measured. To m...
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There are a number of human diseases that are caused by the epistatic Interaction of multiple genes. detecting these interactions with standard statistical tools is difficult, because there may be an interaction effec...
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Reciprocal altruism and inclusive fitness are generally considered alternative mechanisms by which cooperative, altruistic traits may evolve. Here we demonstrate that very general versions of Hamilton's inclusive ...
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ISBN:
(纸本)0780385152
Reciprocal altruism and inclusive fitness are generally considered alternative mechanisms by which cooperative, altruistic traits may evolve. Here we demonstrate that very general versions of Hamilton's inclusive fitness rule (developed by Queller) can be applied to traditional reciprocal altruism models such as the iterated Prisoner's dilemma. In this way we show that both mechanisms rely fundamentally on the same principle - the positive assortment of helping behaviors. We discuss barriers to this unified view, including phenotype/genotype differences and non-additive fitness (or utility) functions that are typical of reciprocal altruism models. We then demonstrate how Queller's versions of Hamilton's rule remove these obstacles.
作者:
Barry WellmanAnabel Quan-HaaseJeffrey BoaseWenhong ChenKeith HamptonIsabel díazKakuko MiyataIn 1965
moved from his Bronx High School of Science slide rule to IBM cards and an 029 keypunch in the bowels of Harvard University. Since then he's been primarily interested in the interplay between large-scale social processes and how people use technology to be connected at work and in the community. His NetLab research network is trying to get a handle on how the Internet fits into everyday life. Wellman founded the International Network for Social Network Analysis in 1976. He is a recent Chair of the Community section of the American Sociological Association has been nominated for the Chair of the Communication and Information Technology section of the ASA the Virtual Community focus area leader for SIGGROUP/ACM and a Executive Cmmittee member of the Association for Internet Researchers. Wellman's (co)edited books are: Social Structures: A Network Approach (2d ed CSPI 2003) Networks in the Global Village (Westview Press
1999) and The Internet in Everyday Life (Blackwell Publishers 2002). Address:Centre for Urban & Community Studies
University of Toronto 455 Spadina Avenue Toronto Canada M5S 2G8. Fax: +1-416-978-7162 Address:Centre for Urban & Community Studies
University of Toronto 455 Spadina Avenue Toronto M5S 2G8 Canada. Address:Massachusetts Institute of Technology
77 Mass. Ave. Room 9-522 Cambridge MA 02139. Address:IN3
Av. Tibidabo 47 08035 Barcelona Spain. Phone: +*** Fax: +***. Address:Department of Sociology
Meiji Gakuin University 1-2-37 Shirokanedai Minato-ku Tokyo 108-8636 JAPAN. Phone: +81-3-5421-5565 Fax: +81-3-5421-5697. Doctoral student at the Faculty of Information Studies
University of Toronto. She has been a Fellow of the Knowledge Media Design Institute and the McLuhan Program in Culture and Technology. Her articles address the nature of Internet-related social change for social integration and information flow. Her articles have examined the implications of these changes for communities and her thesis focuses on organizations. University of Toronto doctoral
We review the evidence from a number of surveys in which our NetLab has been involved about the extent to which the Internet is transforming or enhancing community. The studies show that the Internet is used for conne...
We review the evidence from a number of surveys in which our NetLab has been involved about the extent to which the Internet is transforming or enhancing community. The studies show that the Internet is used for connectivity locally as well as globally, although the nature of its use varies in different countries. Internet use is adding on to other forms of communication, rather than replacing them. Internet use is reinforcing the pre-existing turn to societies in the developed world that are organized around networked individualism rather than group or local solidarities. The result has important implications for civic involvement.
Adaptive Critic methods, which approximate dynamic programming, have been used successfully for solving optimal control problems. The Adaptive Critic learning algorithm optimizes a secondary utility function that is t...
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Adaptive Critic methods, which approximate dynamic programming, have been used successfully for solving optimal control problems. The Adaptive Critic learning algorithm optimizes a secondary utility function that is the sum of the present and an future primary utility. The primary utility function measures the instantaneous cost incurred for the last action taken and the resulting state. The motivation for using a fuzzy primary utility function comes from the set of control problems for which there is only a qualitative definition of performance - for example, success or failure. Previous work in applying Adaptive Critic methods to this type of problem showed that a crisp definition of success resulted in solutions that met the control objective, but in an undesirable manner. An appropriate fuzzy utility function, on the other hand, is able to generate the optimal solution. Another motivation for incorporating fuzzy techniques into the utility function is to overcome measurement noise. Measurement noise has a significant adverse effect on the reliability and speed of Adaptive Critic learning;by incorporating fuzzy sets into the utility function, the effect of the noise can be mitigated.
Adaptive Critic methods for reinforcement learning are known to provide consistent solutions to optimal control problems, and are also considered plausible models for cognitive learning processes. This paper discusses...
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ISBN:
(纸本)0780383591
Adaptive Critic methods for reinforcement learning are known to provide consistent solutions to optimal control problems, and are also considered plausible models for cognitive learning processes. This paper discusses binary reinforcement in the context of three Adaptive Critic methods: Heuristic dynamic programming (HdP), dual Heuristic programming (dHP), and Globalizeddual Heuristic programming (GdHP). Binary reinforcement arises when the qualitative measure of success is simply "pass" or "fail". We implement binary reinforcement with Adaptive Critic methods for the pole-cart benchmark problem. Results demonstrate two qualitatively dissimilar classes of controllers: those that replicate the system stabilization achieved with quadratic utility, and those that merely succeed at not dropping the pole. It is found that the GdHP method is effective for learning an approximately optimal solution, with results comparable to those obtained via dHP that uses a more informative, quadratic utility function.
Reciprocal altruism and inclusive fitness are generally considered alternative mechanisms by which cooperative, altruistic traits may evolve. Here we demonstrate that very general versions of Hamilton's inclusive ...
详细信息
Reciprocal altruism and inclusive fitness are generally considered alternative mechanisms by which cooperative, altruistic traits may evolve. Here we demonstrate that very general versions of Hamilton's inclusive fitness rule (developed by Queller) can be applied to traditional reciprocal altruism models such as the iterated prisoner's dilemma. In this way we show that both mechanisms rely fundamentally on the same principle - the positive assortment of helping behaviors. We discuss barriers to this unified view, including phenotype/genotype differences and nonadditive fitness (or utility) functions that are typical of reciprocal altruism models. We then demonstrate how Queller's versions of Hamilton's rule remove these obstacles.
Cellular receptor dynamics are often analyzed using differential equations, making system dynamics (Sd) a candidate methodology. In some cases it may be useful to model the phenomena at the biomolecular level, especia...
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Cellular receptor dynamics are often analyzed using differential equations, making system dynamics (Sd) a candidate methodology. In some cases it may be useful to model the phenomena at the biomolecular level, especially when concentrations and reaction probabilities are low and might lead to unexpected behavior modes. In such cases, agent-based simulation (ABS) may be useful. We show the application of both Sd and ABS to simulate non-equilibrium ligand-receptor dynamics over a broad range of concentrations, where the probability of interaction varies from low to very low. Both approaches offer much to the researcher and are complementary. We did not find a clear demarcation indicating when one paradigm or the other would be strongly preferred, although Sd is an obvious choice when studying systems at a high level of aggregation and abstraction, and ABS is well suited to studying phenomena at the level of individual receptors and molecules.
Adaptive critic methods, which approximate dynamic programming, have been used successfully for solving optimal control problems. The adaptive critic learning algorithm optimizes a secondary utility function that is t...
详细信息
Adaptive critic methods, which approximate dynamic programming, have been used successfully for solving optimal control problems. The adaptive critic learning algorithm optimizes a secondary utility function that is the sum of the present and all future primary utility. The primary utility function measures the instantaneous cost incurred for the last action taken and the resulting state. The motivation for using a fuzzy primary utility function comes from the set of control problems for which there is only a qualitative definition of performance - for example, success or failure. Previous work in applying adaptive critic methods to this type of problem showed that a crisp definition of success resulted in solutions that met the control objective, but in an undesirable manner. An appropriate fuzzy utility function, on the other hand, is able to generate the optimal solution. Another motivation for incorporating fuzzy techniques into the utility function is to overcome measurement noise. Measurement noise has a significant adverse effect on the reliability and speed of adaptive critic learning; by incorporating fuzzy sets into the utility function, the effect of the noise can be mitigated.
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