Some numerical methods for solving stochastic impulse control in natural gas storage facilities

The valuation of gas storage facilities is characterized as a stochastic impulse control problem with finite horizon resulting in Hamilton-Jacobi-Bellman (HJB) equations for the value function. In this context the two catagories of solving schemes for optimal switching are discussed in a stochastic control framework. We reviewed some numerical methods which include approaches related to partial differential equations (PDEs), Markov chain approximation, nonparametric regression, quantization method and some practitioners’ methods. This paper considers optimal switching problem arising in valuation of gas storage contracts for leasing the storage facilities, and investigates the recent developments as well as their advantages and disadvantages of each scheme based on dynamic programming principle (DPP

Is Strong Reciprocity a Maladaptation? On the Evolutionary Foundations of Human Altruism

In recent years a large number of experimental studies have documented the existence of strong reciprocity among humans. Strong reciprocity means that people willingly repay gifts and punish the violation of cooperation and fairness norms even in anonymous one-shot encounters with genetically unrelated strangers. We provide ethnographic and experimental evidence suggesting that ultimate theories of kin selection, reciprocal altruism, costly signaling and indirect reciprocity do not provide satisfactory evolutionary explanations of strong reciprocity. The problem of these theories is that they can rationalize strong reciprocity only if it is viewed as maladaptive behavior whereas the evidence suggests that it is an adaptive trait. Thus, we conclude that alternative evolutionary approaches are needed to provide ultimate accounts of strong reciprocity.

Cooperative Game Theory within Multi-Agent Systems for Systems Scheduling

Research concerning organization and coordination within multi-agent systems continues to draw from a variety of architectures and methodologies. The work presented in this paper combines techniques from game theory and multi-agent systems to produce self-organizing, polymorphic, lightweight, embedded agents for systems scheduling within a large-scale real-time systems environment. Results show how this approach is used to experimentally produce optimum real-time scheduling through the emergent behavior of thousands of agents. These results are obtained using a SWARM simulation of systems scheduling within a High Energy Physics experiment consisting of 2500 digital signal processors.Comment: Fourth International Conference on Hybrid Intelligent Systems (HIS), Kitakyushu, Japan, December, 200

Naturalizing institutions: Evolutionary principles and application on the case of money

In recent extensions of the Darwinian paradigm into economics, the replicator-interactor duality looms large. I propose a strictly naturalistic approach to this duality in the context of the theory of institutions, which means that its use is seen as being always and necessarily dependent on identifying a physical realization. I introduce a general framework for the analysis of institutions, which synthesizes Searle's and Aoki's theories, especially with regard to the role of public representations (signs) in the coordination of actions, and the function of cognitive processes that underly rule-following as a behavioral disposition. This allows to conceive institutions as causal circuits that connect the population-level dynamics of interactions with cognitive phenomena on the individual level. Those cognitive phenomena ultimately root in neuronal structures. So, I draw on a critical restatement of the concept of the meme by Aunger to propose a new conceptualization of the replicator in the context of institutions, namely, the replicator is a causal conjunction between signs and neuronal structures which undergirds the dispositions that generate rule-following actions. Signs, in turn, are outcomes of population-level interactions. I apply this framework on the case of money, analyzing the emotions that go along with the use of money, and presenting a stylized account of the emergence of money in terms of the naturalized Searle-Aoki model. In this view, money is a neuronally anchored metaphor for emotions relating with social exchange and reciprocity. Money as a meme is physically realized in a replicator which is a causal conjunction of money artefacts and money emotions. --Generalized Darwinism,institutions,replicator/interactor,Searle,Aoki,naturalism,memes,emotions,money

Aging and risk taking: toward an integration of cognitive, emotional, and neurobiological perspectives

In this article, we characterize the relationship between natural aging and risky decision making through an integration of cognitive, emotional, and neurobiological theories on the effects of natural aging. Based on the existing evidence, we propose that the positivity emotional bias in elderly adults steers them away from taking high risks and toward more conservative approaches during decision making as part of their positive emotional regulatory strategies. However, aging is also associated with marked declines in cognitive functioning, such as attention and working memory, as well as impaired reinforcement-based associative learning, which arises from anatomical and functional declines in the dopaminergic transmission systems and in distinct brain regions such as the dorsolateral prefrontal cortex and hippocampus. In consequence, elderly adults may deviate from their usual conservative stance and toward more risk-taking tendencies, as observed in a subset of studies, if the demands of the risk-taking task exceed their cognitive and learning capacities. More empirical investigations are needed to determine the key factors that influence elderly individuals' decision making and behavior in risky situations. Research in this field is likely to have important practical implications for the financial and medical decision making of elderly adults, as well as promoting designated help targeting the elderly population in making important life decisions.published_or_final_versio