tailieunhanh - Simulation of Biological Processes phần 3

mô hình mô phỏng một phần hiện tượng thông qua các xấp xỉ đơn giản hóa. Vì vậy chúng ta thấy rằng sự khác biệt giữa phương pháp tiếp cận mô hình trở nên phần nào tùy ý, như tất cả các mô hình là các mô hình hiện tượng. Các di ¡erences không phải là chất lượng nhưng số lượng, và liên quan đến số lượng của các biến và các thông số chúng tôi rất vui để cắm vào bộ não của chúng tôi hoặc vào các mạch của một máy tính. . | 44 KRAKAUER make simulation models partially phenomenological through simplifying approximations. We see therefore that the distinction between modelling approaches becomes somewhat arbitrary as all models are phenomenological models. The differences are not qualitative but quantitative and relate to the number of variables and parameters we are happy to plug into our brains or into the circuitry of a computer. A smaller number of variables and parameters is always preferable but our willingness to move toward the phenomenological depends on how reliable is the derivation of the macroscopic equations from the microscopic interactions. A formal approach to rescaling many-body problems a method for reducing the number of variables is to use renormalization group theory Wilson 1979 . Here I am going to present an evolutionary perspective on this complex topic. Rather than discuss Monte Carlo methods agent based models interacting particle systems and stochastic and deterministic models and their uses at each scale. I restrict myself to a biological justification for phenomenological modelling. The argument is as follows. Natural selection works through the differential replication of individuals. Individuals are complex aggregates and yet the fitness of individuals is a scalar quantity not a vector of component fitness contributions. This implies that the design of each component of an aggregate must be realized through the differential replication of the aggregate as a whole. We are entitled therefore to characterize the aggregate with a single variable fitness rather than enumerate variables for all of its components. This amounts to stating that identifying levels of selection can be an effective procedure for reducing the dimensionality of our state space. Levels of selection Here I shall briefly summarize current thinking on the topic of units and levels of selection for useful reviews see Keller 1999 Williams 1995 . The levels of selection are those units of .