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Libros sobre el tema "Agents behaviour"

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Publicado: 14 de septiembre de 2024

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1

Aghajan, Hamid K. y Björn Gottfried. Behaviour monitoring and interpretation: BMI : well-being. Amsterdam, The Netherlands: IOS Press, 2011.

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2

1943-, Joseph M. H., ed. Monitoring neurotransmitter release during behaviour. Weinheim, Federal Republic of Germany: VCH, 1986.

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3

Björn, Gottfried y Aghajan Hamid K, eds. Behaviour monitoring and interpretation - BMI: Smart environments. Amsterdam: IOS Press, 2009.

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4

Chan, Chris Chi-Yet. Behaviour of metals in MSW incinerator fly ash during roasting with chlorinating agents. Ottawa: National Library of Canada = Bibliothèque nationale du Canada, 1997.

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5

Filipowicz, Judy Rachel. Using ART 1 (Adaptive Resonance Theory 1) to Study Flocking Behaviour in Intelligent agents. Oxford: Oxford Brookes University, 2001.

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6

C, Billari Francesco, Prskawetz Alexia y Workshop on Agent-Based Computational Demography (2001 : Rostock, Germany), eds. Agent-based computational demography: Using simulation to improve our understanding of demographic behaviour. New York: Springer, 2003.

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7

Gupta, Indrani. Treatment-seeking behaviour and the willingness to pay for antiretroviral therapy of HIV positive patients in India. Delhi: Institute of Economic Growth, 2003.

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8

Corkum, Mary Jane. Consequences of social stress and the influence of flavouring agents on ingestive behaviour of feedlot steers. Charlottetown: University of Prince Edward Island, 1992.

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9

Vellakkal, Sukumar. Adverse selection and private health insurance coverage in India: A rational behaviour model of insurance agents under asymmetric information. New Delhi: Indian Council for Research on International Economic Relations, 2009.

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10

Bordignon, Massimo. An investigation in the theory of voluntary provision of public goods and income tax evasion under the hypothesisof ethical behaviour on the part of economic agents. [s.l.]: typescript, 1989.

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11

Rakesh, Duggal y Cudd Mike, eds. Agency behavior. Patrington: Barmarick, 1998.

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12

1937-, Zana Raoul y Xia Jiding 1921-, eds. Gemini surfactants: Synthesis, interfacial and solution-phase behavior, and applications. New York: Marcel Dekker, 2004.

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13

Secchi, Davide y Martin Neumann, eds. Agent-Based Simulation of Organizational Behavior. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-18153-0.

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14

Alonso-Betanzos, Amparo, Noelia Sánchez-Maroño, Oscar Fontenla-Romero, J. Gary Polhill, Tony Craig, Javier Bajo y Juan Manuel Corchado, eds. Agent-Based Modeling of Sustainable Behaviors. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-46331-5.

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15

I, Selverston Allen, ed. Model neural networks and behavior. New York: Plenum Press, 1985.

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16

Sue, Dopson y Mark Annabelle, eds. Organisational behaviour in health care: The research agenda. Basingstoke: Macmillan, 1999.

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17

Karsa, David. Surface Active Behaviour of Performance Surfactants. Wiley & Sons, Limited, John, 2000.

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18

McPhail, Alexander. Learning and Behaviour. Lucid Press, 2003. http://dx.doi.org/10.51669/natphil-001/.

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A miser gains advantage by playing a certain fixed strategy. Any agent that employs an adapting strategy will be enslaved. Two misers must eventually agree to cooperate. By eliminating defectors, a population of agents can benefit from synergies.
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19

Karsa, David R. Surface Active Behaviour of Performance Surfactants (Annual Surfactants Review). 3a ed. Blackwell, 2000.

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20

Chin, Chien Ting. Modelling the behaviour of microbubble contrast agents for diagnostic ultrasound. 2001.

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21

Bank Behaviour And Resilience Effect Of Structures Institutions And Agents. Palgrave MacMillan, 2012.

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22

Hrdina, Pavel D. y Radhey L. Singhal. Neuroendocrine Regulation and Altered Behaviour. Springer London, Limited, 2012.

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23

Behaviour monitoring and interpretation - BMI: Smart environments. Amsterdam: IOS Press, 2009.

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24

Bakir, Caner. Bank Behaviour and Resilience: The Effect of Structures, Institutions and Agents. Palgrave Macmillan, 2013.

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25

Bakir, C. Bank Behaviour and Resilience: The Effect of Structures, Institutions and Agents. Palgrave Macmillan Limited, 2013.

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26

Bakir, C. Bank Behaviour and Resilience: The Effect of Structures, Institutions and Agents. Palgrave Macmillan Limited, 2013.

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27

Chambers, Robert G. Competitive Agents in Certain and Uncertain Markets. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190063016.001.0001.

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This book uses concepts from optimization theory to develop an integrated analytic framework for treating consumer, producer, and market equilibrium analyses as special cases of a generic optimization problem. The same framework applies to both stochastic and non-stochastic decision settings, so that the latter is recognized as an (important) special case of the former. The analytic techniques are borrowed from convex analysis and variational analysis. Special emphasis is given to generalized notions of differentiability, conjugacy theory, and Fenchel's Duality Theorem. The book shows how virtually identical conjugate analyses form the basis for modeling economic behavior in each of the areas studied. The basic analytic concepts are borrowed from convex analysis. Special emphasis is given to generalized notions of differentiability, conjugacy theory, and Fenchel's Duality Theorem. It is demonstrated how virtually identical conjugate analyses form the basis for modelling economic behaviour in each of the areas studied.
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28

Billari, Francesco C. y Alexia Prskawetz. Agent-Based Computational Demography: Using Simulation to Improve Our Understanding of Demographic Behaviour. Physica-Verlag, 2012.

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29

Lugrin, Birgit, Catherine Pelachaud y David Traum. Handbook on Socially Interactive Agents : 20 Years of Research on Embodied Conversational Agents, Intelligent Virtual Agents, and Social Robotics, Volume 1: Establishing SIA Research, Appearance and Behaviour, Social Cognition. Morgan & Claypool Publishers, 2021.

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30

Agent-Based Computational Demography: Using Simulation to Improve Our Understanding of Demographic Behaviour (Contributions to Economics). Physica-Verlag Heidelberg, 2003.

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31

Adverse selection and private health insurance coverage in India: A rational behaviour model of insurance agents under asymmetric information. New Delhi: Indian Council for Research on International Economic Relations, 2009.

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32

Holland, John H. 3. Complex adaptive systems (CAS). Oxford University Press, 2014. http://dx.doi.org/10.1093/actrade/9780199662548.003.0003.

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Complex adaptive systems (CAS) are composed of elements, called agents, that learn or adapt in response to interactions with other agents. ‘Complex adaptive systems’ shows that all CAS exhibit lever points, points where a small directed action causes large predictable changes in aggregate behaviour. All CAS agents have three levels of activity: performance (moment-by-moment capabilities), credit-assignment (rating the usefulness of available capabilities), and rule-discovery (generating new capabilities). The behaviour of a CAS is always generated by the adaptive interactions of its components; and the hierarchical structure characteristic of CAS is also generated—particular combinations of agents at one level become agents at the next higher level.
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33

Hill, David y Helen Dixon. Achieving behavioural changes in individuals and populations. Oxford University Press, 2013. http://dx.doi.org/10.1093/med/9780199550173.003.0003.

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Chapter 3 considers how behavioural theory and research can be translated into successful cancer prevention programmes. Such programmes may be applied at the individual, group, community or national level. The agenda for behavioural interventions in cancer prevention is set by rigorous epidemiological analysis. The ultimate goal of behavioural interventions is to enable individuals to reduce their cancer risk by engaging in recommended preventive behaviours. To reach this goal, a thorough analysis of factors underpinning the behaviour in question is needed to identify possible targets for intervention. This foundation can be strengthened by consideration of key psychological principles known to be important drivers of health-related behaviour. Chapter 3 presents the Big Five Principles of Behaviour Change and suggest how they may be applied to promoting and evaluating change in cancer preventive behaviour.
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34

Warwick, University of, ed. An investigation in the theory of voluntary provision of public goods and income tax evasion under the hypothesis of ethical behaviour on the part of economic agents. 1989.

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35

Artificial Intelligence – Agent Behaviour. Bookboon.com, 2013.

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36

Artificial Intelligence – Agent Behaviour. Bookboon.com, 2013.

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37

Artificial Intelligence – Agent Behaviour. Bookboon.com, 2013.

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38

Artificial Intelligence – Agent Behaviour. Bookboon.com, 2013.

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39

Artificial Intelligence – Agent Behaviour. Bookboon.com, 2013.

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40

Cromey, Catherine y Susan Catling. Adjuvant drugs in neuraxial anaesthesia. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198713333.003.0017.

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The addition of adjuvants to local anaesthetics for use in labour epidurals or for intrathecal administration is common practice in obstetric anaesthesia. This chapter provides an overview of the pharmacology of receptors within the epidural and intrathecal spaces and discusses the options available. Adjuncts are classified as opioid and non-opioid and each agent is explored in detail. The mechanism of action, clinical uses, effective dose ranges, speeds of onset and duration, side effects, disadvantages, and special circumstances associated with each agent are explored. Where formal guidelines exist, these are discussed in detail. Although large randomized controlled trial data is lacking, information regarding current knowledge of the behaviour of these agents in obstetric and non-obstetric practice is presented to assist clinicians when deciding about the appropriateness of each agent for their individual practice.
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41

de Marchi, Scott y Scott E. Page. Agent‐Based Modeling. Editado por Janet M. Box-Steffensmeier, Henry E. Brady y David Collier. Oxford University Press, 2009. http://dx.doi.org/10.1093/oxfordhb/9780199286546.003.0004.

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This article provides a discussion on agent-based modeling. Two examples that show the ability of computational methods to extend game-theoretic results are presented. It then discusses modeling agents, modeling agent interactions, and system behaviour. In addition, it describes how agent-based models differ from and complement mathematical models and concludes with some suggestions for how one might best leverage the strengths of agent-based models to advance political science. Most mathematical analyses of game-theoretic models do not look into the stability and attainability of their equilibria and would be made richer by complementing them with agent-based models that explored those properties. The ability of computational models to test the robustness of formal results would be reason alone to add them to tool kits. As a methodology, agent-based modeling should be considered as in its infancy, its enormous potential limited only by the scientific and creative talents of its practitioners.
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42

Carli, Linda L. Social Influence and Gender. Editado por Stephen G. Harkins, Kipling D. Williams y Jerry Burger. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199859870.013.16.

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This chapter reviews current research on gender and social influence. Overall, men exert greater influence than women do. Women’s disadvantage derives from gender stereotypes that characterize men as more competent and agentic than women and that require women to be more selfless and communal than men. Both agentic and communal behaviors predict influence. As a result, women are subjected to a double bind. They may lack influence because of doubt about their competence, or they may lack influence because their competent behavior elicits concern that they are insufficiently communal. In contrast, men have greater behavioral flexibility than women do as influence agents. Men tend to be more resistant to women’s influence than women are, particularly when female influence agents behave in a highly competent manner. Resistance to female influence can be reduced in contexts that are stereotypically feminine and when women display a blend of agentic and communal qualities.
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43

Patisaul, Heather B. y Scott M. Belcher. Endocrine Disruptors, Brain, and Behavior. Oxford University Press, 2017.

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44

Di Paolo, Ezequiel A., Thomas Buhrmann y Xabier E. Barandiaran. The missing theory of agency. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780198786849.003.0005.

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The sensorimotor approach emphasizes the significance of action as a determinant of perception, implicitly assuming an agent who engages in intentional actions serving his own interest. It has yet to concern itself with the origin of the norms guiding the agent’s behavior or with a definition of what an agent even is. The chapter examines how the enactive approach can fill this gap. It promotes a theory of agency grounded in the organizational properties of living systems and identifies three requirements—self-individuation, interactional asymmetry, and normativity—that are individually necessary and jointly sufficient to determine whether a system is an agent. The usefulness of the theory is tested by examining whether different systems satisfy these conditions. The chapter contributes to the conceptual clarification of the sensorimotor approach by showing how the notion of agency leads to an understanding of an organism’s sensors and effectors that goes beyond arbitrary anatomical distinctions.
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45

Okasha, Samir. Can Adaptiveness and Rationality Part Ways? Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198815082.003.0008.

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Given the abstract parallel between fitness and utility, it is natural to think that adaptive behaviour and rational behaviour will typically coincide, as many authors assume. However, a series of arguments, found in the philosophy, behavioural ecology, and economics literatures, suggest that in some cases the adaptive and the rational can part ways: evolution favours behaviours that violate the principles of rational choice. These ‘parting-of-ways’ arguments pose a challenge to agential thinking in biology—that is, to the idea that an evolved organism can be treated as akin to a rational agent pursuing a goal. However, in many cases the parting may be eliminated by suitable choice of utility function or fitness measure, or by reframing the decision problem.
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46

Laughlin, Robert G. Aqueous Phase Behavior of Surfactants. Elsevier Science & Technology Books, 1996.

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47

Furchtgott, Ernest. Pharmacological and Biophysical Agents and Behavior. Elsevier Science & Technology Books, 2013.

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48

Lardeux, Raphaël. Public Finance with Behavioural Agents. Cambridge University Press, 2022.

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49

Lardeux, Raphaël. Public Finance with Behavioural Agents. Cambridge University Press, 2022.

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50

Bohnet, Iris, Benedikt Herrmann, Maliheh Paryavi, Anh Tran y Richard Zeckhauser. Improving Outcomes in the Trust Game. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190630782.003.0013.

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This chapter examines how people in Oman, the United States, and Vietnam deal with trust situations. It offers two trust-fostering mechanisms—a mitigation-based approach (“insurance”), decreasing the principal’s cost of betrayal, and a prevention-based approach (“bonus”), increasing the agent’s benefits of trustworthiness. What choices principals make were measured, as well as how agents respond to them and how both parties’ behaviors compare to a situation where insurance or bonus was assigned by chance. About two-thirds of our principals prefer the safety of the insurance mechanism and about one-third prefer sending a bonus, making themselves vulnerable to the agent. This vulnerability pays off by tripling the likelihood of trustworthiness compared to when insurance is chosen. Still, when a bonus is chosen, only about half of the agents reward trust. This fraction is insufficient to make the principals whole. In terms of expected payoffs principals would be better off with insurance.
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