120,649 research outputs found

    An evolutionary behavioral model for decision making

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    For autonomous agents the problem of deciding what to do next becomes increasingly complex when acting in unpredictable and dynamic environments pursuing multiple and possibly conflicting goals. One of the most relevant behavior-based model that tries to deal with this problem is the one proposed by Maes, the Bbehavior Network model. This model proposes a set of behaviors as purposive perception-action units which are linked in a nonhierarchical network, and whose behavior selection process is orchestrated by spreading activation dynamics. In spite of being an adaptive model (in the sense of self-regulating its own behavior selection process), and despite the fact that several extensions have been proposed in order to improve the original model adaptability, there is not a robust model yet that can self-modify adaptively both the topological structure and the functional purpose\ud of the network as a result of the interaction between the agent and its environment. Thus, this work proffers an innovative hybrid model driven by gene expression programming, which makes two main contributions: (1) given an initial set of meaningless and unconnected units, the evolutionary mechanism is able to build well-defined and robust behavior networks which are adapted and specialized to concrete internal agent's needs and goals; and (2)\ud the same evolutionary mechanism is able to assemble quite\ud complex structures such as deliberative plans (which operate in the long-term) and problem-solving strategies

    Democracy under uncertainty: The ‘wisdom of crowds’ and the free-rider problem in group decision making

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    We introduce a game theory model of individual decisions to cooperate by contributing personal resources to group decisions versus by free-riding on the contributions of other members. In contrast to most public-goods games that assume group returns are linear in individual contributions, the present model assumes decreasing marginal group production as a function of aggregate individual contributions. This diminishing marginal returns assumption is more realistic and generates starkly different predictions compared to the linear model. One important implication is that, under most conditions, there exist equilibria where some, but not all members of a group contribute, even with completely self-interested motives. An agent-based simulation confirms the individual and group advantages of the equilibria in which behavioral asymmetry emerges from a game structure that is a priori perfectly symmetric for all agents (all agents have the same payoff function and action space, but take different actions in equilibria). And a behavioral experiment demonstrates that cooperators and free-riders coexist in a stable manner in groups performing with the non-linear production function. A collateral result demonstrates that, compared to a ―dictatorial‖ decision scheme guided by the best member in a group, the majority-plurality decision rules can pool information effectively and produce greater individual net welfare at equilibrium, even if free-riding is not sanctioned. This is an original proof that cooperation in ad hoc decision-making groups can be understood in terms of self-interested motivations and that, despite the free-rider problem, majority-plurality decision rules can function robustly as simple, efficient social decision heuristics.group decision making under uncertainty, free-rider problem, majority-plurality rules, marginally-diminishing group returns, evolutionary games, behavioral experiment

    On modeling social diffusion under the impact of dynamic norms

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    We develop and analyze a collective decision-making model concerning the adoption and diffusion of a novel product, convention, or behavior within a population. Motivated by the growing social psychology literature on dynamic norms, under which an individual is influenced by changing trends in the population, we propose a stochastic model for the decision-making process encompassing two behavioral mechanisms. The first is social influence, which drives coordination among individuals. Consistent with the literature on social diffusion modeling, we capture such a mechanism through an evolutionary game-theoretic framework for a network of interacting individuals. The second, which is the main novelty of our model, represents the impact of dynamic norms, capturing the tendency of individuals to be attracted to products or behaviors with growing popularity. We analytically determine sufficient conditions under which a novel alternative spreads to the majority of the population. Our findings provide insights into the unique and nontrivial role of human sensitivity to dynamic norms in facilitating social diffusion

    Local Orientation and the Evolution of Foraging: Changes in Decision Making Can Eliminate Evolutionary Trade-offs

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    Information processing is a major aspect of the evolution of animal behavior. In foraging, responsiveness to local feeding opportunities can generate patterns of behavior which reflect or “recognize patterns” in the environment beyond the perception of individuals. Theory on the evolution of behavior generally neglects such opportunity-based adaptation. Using a spatial individual-based model we study the role of opportunity-based adaptation in the evolution of foraging, and how it depends on local decision making. We compare two model variants which differ in the individual decision making that can evolve (restricted and extended model), and study the evolution of simple foraging behavior in environments where food is distributed either uniformly or in patches. We find that opportunity-based adaptation and the pattern recognition it generates, plays an important role in foraging success, particularly in patchy environments where one of the main challenges is “staying in patches”. In the restricted model this is achieved by genetic adaptation of move and search behavior, in light of a trade-off on within- and between-patch behavior. In the extended model this trade-off does not arise because decision making capabilities allow for differentiated behavioral patterns. As a consequence, it becomes possible for properties of movement to be specialized for detection of patches with more food, a larger scale information processing not present in the restricted model. Our results show that changes in decision making abilities can alter what kinds of pattern recognition are possible, eliminate an evolutionary trade-off and change the adaptive landscape

    Modeling and Analysis of the Epidemic-Behavior Co-evolution Dynamics with User Irrationality

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    During a public health crisis like COVID-19, individuals' adoption of protective behaviors, such as self-isolation and wearing masks, can significantly impact the spread of the disease. In the meanwhile, the spread of the disease can also influence individuals' behavioral choices. Moreover, when facing uncertain losses, individuals' decisions tend to be irrational. Therefore, it is critical to study individuals' irrational behavior choices in the context of a pandemic. In this paper, we propose an epidemic-behavior co-evolution model that captures the dynamic interplay between individual decision-making and disease spread. To account for irrational decision-making, we incorporate the Prospect Theory in our individual behavior modeling. We conduct a theoretical analysis of the model, examining the steady states that emerge from the co-evolutionary process. We use simulations to validate our theoretical findings and gain further insights. This investigation aims to enhance our understanding of the complex dynamics between individual behavior and disease spread during a pandemic

    Razionalità limitata e regole contrattuali: promesse e problemi della nuova analisi economica del diritto

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    Today Behavioral Law and Economics is the most ambitious attempt to overcome one of the main limits of Law and Economics, that is the recourse to a model of rationality which is little supported by empirical evidence. However, such an attempt relies exclusively on the idea of "cognitive bias" developed by cognitive psychologists Daniel Kahneman and Amos Tversky. From a normative point of view, the implications of that approach are debatable. The paper proposes to look at psychological schools which show stronger links with the original notion of bounded rationality introduced by Herbert Simon. Among these schools, evolutionary psychology rejects the comparison between observed behavior and the axioms of perfect rationality and tries to find out the factors that ease, obstruct or interact with the decision-making process. The differences between the perspective of Behavioral Law and Economics and other psychological approaches are explored in the field of contract law. Moreover, additional considerations are developed on the comparison between the bounded rationality of public and private organizations and its consequences for the allocation of decision-making authority.

    From Bounded Rationality to Behavioral Economics

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    The paper provides an brief overview of the “state of the art” in the theory of rational decision making since the 1950’s, and focuses specially on the evolutionary justification of rationality. It is claimed that this justification, and more generally the economic methodology inherited from the Chicago school, becomes untenable once taking into account Kauffman’s Nk model, showing that if evolution it is based on trial-and-error search process, it leads generally to sub- optimal stable solutions: the ‘as if’ justification of perfect rationality proves therefore to be a fallacious metaphor. The normative interpretation of decision-making theory is therefore questioned, and the two challenging views against this approach , Simon’s bounded rationality and Allais’ criticism to expected utility theory are discussed. On this ground it is shown that the cognitive characteristics of choice processes are becoming more and more important for explanation of economic behavior and of deviations from rationality. In particular, according to Kahneman’s Nobel Lecture, it is suggested that the distinction between two types of cognitive processes – the effortful process of deliberate reasoning on the one hand, and the automatic process of unconscious intuition on the other – can provide a different map with which to explain a broad class of deviations from pure ‘olympian’ rationality. This view requires re-establishing and revising connections between psychology and economics: an on-going challenge against the normative approach to economic methodology.Bounded Rationality, Behavioral Economics, Evolution, As If

    Armin Schulz, Efficient Cognition

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