Biomedical subjects

P M Hui

Publications and source records attributed to P M Hui.

11 recordsLinked to original sources

PubMed2006

Dynamics of opinion formation in a small-world network.

The dynamical process of opinion formation within a model using a local majority opinion updating rule is studied numerically in networks with the small-world geometrical property. The network is one in which shortcuts are added to randomly chosen pairs of nodes in an underlying regular lattice. The presence of a small number of shortcuts is found to shorten the time to reach a consensus significantly. The effects of having shortcuts in a lattice of fixed spatial dimension are shown to be analogous to that of increasing the spatial dimension in regular lattices. The shortening of the consensus time is shown to be related to the shortening of the mean shortest path as shortcuts are added. Results can also be translated into that of the dynamics of a spin system in a small-world network.

Journal Article↗

PubMed2005

Effects of contrarians in the minority game.

We study the effects of the presence of contrarians in an agent-based model of competing populations. Contrarians are common in societies. These contrarians are agents who deliberately prefer to hold an opinion that is contrary to the prevailing idea of the commons or normal agents. Contrarians are introduced within the context of the minority game (MG), which is a binary model for an evolving and adaptive population of agents competing for a limited resource. The average success rate among the agents is found to have a nonmonotonic dependence on the fraction a(c) of contrarians. For small a(c), the contrarians systematically outperform the normal agents by avoiding the crowd effect and enhance the overall success rate. For high a(c), the anti-persistent nature of the MG is disturbed and the few normal agents outperform the contrarians. Qualitative discussion and analytic results for the small a(c) and high a(c) regimes are presented, and the crossover behavior between the two regimes is discussed.

Algorithms↗

PubMed2005

Theory of enhanced performance emerging in a sparsely connected competitive population.

We provide an analytic theory to explain Anghel et al's recent numerical finding whereby a maximum in the global performance emerges for a sparsely connected competitive population [Phys. Rev. Lett. 92, 058701 (2004)]. We show that the effect originates in the highly correlated dynamics of strategy choice, and can be significantly enhanced using a simple modification to the model.

Competitive Behavior↗

PubMed2004

Theory of networked minority games based on strategy pattern dynamics.

We formulate a theory of agent-based models in which agents compete to be in a winning group. The agents may be part of a network or not, and the winning group may be a minority group or not. An important feature of the present formalism is its focus on the dynamical pattern of strategy rankings, and its careful treatment of the strategy ties which arise during the system's temporal evolution. We apply it to the minority game with connected populations. Expressions for the mean success rate among the agents and for the mean success rate for agents with k neighbors are derived. We also use the theory to estimate the value of connectivity p above which the binary-agent-resource system with high resource levels makes the transition into the high-connectivity state.

Adaptation, Physiological↗

PubMed2004

Evolutionary minority game wtih multiple options.

We propose and study an evolutionary minority game (EMG) in which the agents are allowed to choose among three possible options. Unlike the original EMG where the agents either win or lose one unit of wealth, the present model assigns one unit of wealth to the winners in the least popular option, deducts one unit from the losers in the most popular option, and awards R (-1 R(c), where R(c) (N) is a critical value for optimal performance of the system that drops to zero as the number of agents N increases.

Journal Article↗

PubMed2004

Scale-free networks with tunable degree-distribution exponents.

We propose and study a model of scale-free growing networks that gives a degree distribution dominated by a power-law behavior with a model-dependent, hence tunable, exponent. The model represents a hybrid of the growing networks based on popularity-driven and fitness-driven preferential attachments. As the network grows, a newly added node establishes m new links to existing nodes with a probability p based on popularity of the existing nodes and a probability 1-p based on fitness of the existing nodes. An explicit form of the degree distribution P(p,k) is derived within a mean field approach. For reasonably large k, P(p,k) approximately k(-gamma(p)) F(k,p), where the function F is dominated by the behavior of 1/ln (k/m) for small values of p and becomes k independent as p-->1, and gamma(p) is a model-dependent exponent. The degree distribution and the exponent gamma(p) are found to be in good agreement with results obtained by extensive numerical simulations.

Journal Article↗

PubMed2004

Enhanced winning in a competing population by random participation.

We study a version of the minority game in which one agent is allowed to join the game in a random fashion. It is shown that in the crowded regime, i.e., for small values of the memory size m of the agents in the population, the agent performs significantly well if she decides to participate the game randomly with a probability q and she records the performance of her strategies only in the turns that she participates. The information, characterized by a quantity called the inefficiency, embedded in the agent's strategies performance turns out to be very different from that of the other agents. Detailed numerical studies reveal a relationship between the success rate of the agent and the inefficiency. The relationship can be understood analytically in terms of the dynamics in which the various possible histories are being visited as the game proceeds. For a finite fraction of randomly participating agents up to 60% of the population, it is found that the winning edge of these agents persists.

Journal Article↗

PubMed2003

Weighted scale-free networks with stochastic weight assignments.

We propose a model of weighted scale-free networks incorporating a stochastic scheme for weight assignments to the links, taking into account both the popularity and fitness of a node. As the network grows, the weights of links are driven either by the connectivity with probability p or by the fitness with probability 1-p. Numerical results show that the total weight exhibits a power-law distribution with an exponent sigma that depends on the probability p. The exponent sigma decreases continuously as p increases. For p=0, the scaling behavior is the same as that of the connectivity distribution. An analytical expression for the total weight is derived so as to explain the features observed in the numerical results. Numerical results are also presented for a generalized model with a fitness-dependent link formation mechanism.

Journal Article↗

PubMed2002

Finite-size effect in the Eguíluz and Zimmermann model of herd formation and information transmission.

The Eguíluz and Zimmermann model of information transmission and herd formation in a financial market is studied analytically. Starting from a formal description on the rate of change of the system from one partition of agents in the system to another, a mean-field theory is systematically developed. The validity of the mean-field theory is carefully studied against fluctuations. When the number of agents N is sufficiently large and the probability of making a transaction a<<1/N ln N, finite-size effect is found to be significant. In this case, the system has a large probability of becoming a single cluster containing all the agents. For small clusters of agents, the cluster size distribution still obeys a power law but with a much reduced magnitude. The exponent is found to be modified to the value of -3 by the fluctuation effects from the value of -5/2 in the mean-field theory.

Cluster Analysis↗

PubMed2000

Generalized strategies in the minority game.

We show analytically how the fluctuations (i.e., standard deviation sigma) in the minority game can decrease below the random coin-toss limit if the agents use more general, stochastic strategies. This suppression of sigma results from a cancellation between the actions of a crowd, in which agents act collectively and make the same decision, and those of an anticrowd, in which agents act collectively by making the opposite decision to the crowd.

Journal Article↗

PubMed1999

Cellular automaton models of driven diffusive Frenkel-Kontorova-type systems.

Three cellular automaton models of increasing complexity are introduced to model driven diffusive systems related to the generalized Frenkel-Kontorova (FK) models recently proposed by Braun et al. [Phys. Rev. E 58, 1311 (1998)]. The models are defined in terms of parallel updating rules. Simulation results are presented for these models. The features are qualitatively similar to those models defined previously in terms of sequentially updating rules. Essential features of the FK model such as phase transitions, jamming due to atoms in the immobile state, and hysteresis in the relationship between the fraction of atoms in the running state and the bias field are captured. Formulating in terms of parallel updating rules has the advantage that the models can be treated analytically by following the time evolution of the occupation on every site of the lattice. Results of this analytical approach are given for the two simpler models. The steady state properties are found by studying the stable fixed points of a closed set of dynamical equations obtained within the approximation of retaining spatial correlations only up to two nearest-neighboring sites. Results are found to be in good agreement with numerical data.

Journal Article↗