Biomedical subjects

H Fort

Publications and source records attributed to H Fort.

11 recordsLinked to original sources

PubMed2005

Extended estimator approach for 2 x 2 games and its mapping to the Ising Hamiltonian.

We consider a system of adaptive self-interested agents interacting by playing an iterated pairwise prisoner's dilemma (PD) game. Each player has two options: either cooperate (C) or defect (D). Agents have no (long term) memory to reciprocate nor identifying tags to distinguish C from D. We show how their 16 possible elementary Markovian (one-step memory) strategies can be cast in a simple general formalism in terms of an estimator of expected utilities Delta*. This formalism is helpful to map a subset of these strategies into an Ising Hamiltonian in a straightforward way. This connection in turn serves to shed light on the evolution of the iterated games played by agents, which can represent a broad variety of individuals from firms of a market to species coexisting in an ecosystem. Additionally, this magnetic description may be useful to introduce noise in a natural and simple way. The equilibrium states reached by the system depend strongly on whether the dynamics are synchronous or asynchronous and also on the system connectivity.

Journal Article↗

PubMed2004

Self-organization in a simple model of adaptive agents playing 2 x 2 games with arbitrary payoff matrices.

We analyze, both analytically and numerically, the self-organization of a system of "selfish" adaptive agents playing an arbitrary iterated pairwise game (defined by a 2 x 2 payoff matrix). Examples of possible games to play are the prisoner's dilemma (PD) game, the chicken game, the hero game, etc. The agents have no memory, use strategies not based on direct reciprocity nor "tags" and are chosen at random, i.e., geographical vicinity is neglected. They can play two possible strategies: cooperate (C) or defect (D). The players measure their success by comparing their utilities with an estimate for the expected benefits and update their strategy following a simple rule. Two versions of the model are studied: (1) the deterministic version (the agents are either in definite states C or D) and (2) the stochastic version (the agents have a probability c of playing C). Using a general master equation we compute the equilibrium states into which the system self-organizes, characterized by their average probability of cooperation c(eq). Depending on the payoff matrix, we show that c(eq) can take five different values. We also consider the mixing of agents using two different payoff matrices and show that any value of c(eq) can be reached by tuning the proportions of agents using each payoff matrix. In particular, this can be used as a way to simulate the effect of a fraction d of "antisocial" individuals--incapable of realizing any value to cooperation--on the cooperative regime hold by a population of neutral or "normal" agents.

Journal Article↗

PubMed2003

Cooperation and self-regulation in a model of agents playing different games.

A simple model for cooperation between "selfish" agents, which play an extended version of the prisoner's dilemma game, in which they use arbitrary payoffs, is presented and studied. A continuous variable, representing the probability of cooperation, p(k)(t) in [0,1], is assigned to each agent k at time t. At each time step t a pair of agents, chosen at random, interact by playing the game. The players update their p(k)(t) using a criterion based on the comparison of their utilities with the simplest estimate for expected income. The agents have no memory and do not use strategies based on direct reciprocity or "tags." Depending on the payoff matrix, the system self-organizes-after a transient-into stationary states characterized by their average probability of cooperation p(eq) and average equilibrium per-capita income p(eq),U(infinity). It turns out that the model exhibits some results that contradict the intuition. In particular, some games that a priori seem to favor defection most, may produce a relatively high degree of cooperation. Conversely, other games, which one would bet lead to maximum cooperation, indeed are not the optimal for producing cooperation.

Journal Article↗

PubMed2002

Model for mutation in bacterial populations.

We describe the evolution of E. coli populations through a Bak-Sneppen-type model which incorporates random mutations. We show that, for a value of the mutation level which coincides with the one estimated from experiments, this model reproduces the measures of mean fitness relative to that of a common ancestor, performed for over 10,000 bacterial generations.

Biological Evolution↗

PubMed1996