4 Presentations

• 
  10:40 AM - 11:05 AM

  Evolutionary prey pairing strategy against optimal foragers

  • Fei Xu, presenter, Wilfrid Laurier University

  Pairing strategy enables prey species to obtain certain protection against predators. By forming a pair with another prey, a prey may lower the chance of being caught and thus has increased payoff. In this work, we integrate such pairing strategy of prey species into the dynamics of a food web system containing a predator species and two prey species, in which each species behave strategically to maximize its per capita population growth rate. We perform analysis to reveal the interaction between these species with game theory-based behavioral strategies.

• 
  11:05 AM - 11:30 AM

  Tax Collection under Information Spreading in Structured Population

  • Elena Gubar, presenter, St.Petersburg State University
  • Suriya Kumacheva, St.Petersburg State University
  • Ekaterina Zhitkova, St.Petersburg State University
  • Galina Tomilina, St.Petersburg State University

  Nowadays information is an important tool of the taxation system. All participants of the tax relations – tax authority and taxpayers allow using information to increase their profit function. Based on the previous research where inefficiency of the total tax audit was shown, we consider a model of tax control which includes a process of propagation of information to stimulate the tax collection. Here we suppose that every agent chooses her behavior depending on her own risk propensity, information received from her contact network and economic environment. We set that in well-mixed population of taxpayers every agent has different propensity to a risk: risk averse, risk neutral and risk loving. The structure of population of taxpayers is given by the networks of different topology, where nodes are agents and links are the connections between them. Received information corrects taxpayer’s behavior and helps tax authority to maintain the necessary level of tax collection. We formulate an evolutionary model of tax control and analyze the behavior of agents based on Markov process and the imitation rule. We estimate the influence of structure of the network to the process of propagation information. Theoretical approach is supported by the series of experiments which illustrate different economic scenarios.

• 
  11:30 AM - 11:55 AM

  Evolutionary tax evasion and optimal regulation under prospect theory

  • Fabio Lamantia, presenter, University of Calabria
  • Domenico De Giovanni, University of Calabria
  • Mario Pezzino, University of Manchester

  The paper studies the dynamics of compliance in a population of agents that decide whether to engage in tax evasion depending on an evolutionary adaptation process. Payoffs are assumed to have the realistic features of Prospect Theory utilities. The paper also considers an optimal control problem to study the long-run level of tax evasion when a tax authority attempts to maximize the expected stream of tax revenues choosing auditing effort. The analysis provides conditions for the evolution of tax evasion to converge to an asymptotically stable interior equilibrium where only a portion of the population engages in tax evasion. Moreover, the study of the intertemporal optimal auditing produces novel and rich results, including the existence of multiple equilibria and discontinuities in the optimal control.

• 
  11:55 AM - 12:20 PM

  Darwin’s Finches and Darwinian Dynamics: Predicting beak strategies on the Galapagos Islands

  • Tania L.S. Vincent, Anchorage, AK 99504
  • Joseph Apaloo, presenter, St. Francis Xavier University
  • Thomas L. Vincent, University of Arizona, Tucson, AZ 85721

  Using field data on Galapagos finches collected by Dolph Schluter and Peter Grant in 1984, a modified Lotka-Volterra competition model, and evolutionary game theory, we explore a model of evolution of ground-finch communities on 15 Galapagos Islands. Our results reveal several important implications about the evolution of community structure. First, we predict that evolutionarily stable strategies (ESSs) do not always occur at potential carrying capacity “peaks.” Second, we predict that communities with strategies that do occur at carrying capacity "peaks" can exhibit reduced frequency-dependent competition and even “ghost of competition past.” These predictions are important because they reveal a testable mechanism behind patterns of community structure we see today.