Groupthink occurs when everyone in a group starts thinking alike, as when people put unlimited faith in a leader. Avoiding this phenomenon is a ubiquitous challenge to problem-solving enterprises and typical countermeasures involve the mobility of group members. Here we use an agent-based model of imitative learning to study the influence of the mobility of the agents on the time they require to find the global maxima of NK-fitness landscapes. The agents cooperate by exchanging information on their fitness and use this information to copy the fittest agent in their influence neighborhoods, which are determined by face-to-face interaction networks. The influence neighborhoods are variable since the agents perform random walks in a two-dimensional space. We find that mobility is slightly harmful for solving easy problems, i.e., problems that do not exhibit suboptimal solutions or local maxima. For difficult problems, however, mobility can prevent the imitative search being trapped in suboptimal solutions and guarantees a better performance than the independent search for any system size.

In this paper we revisited the Ziff-Gulari-Barshad model to study its phase transitions and critical exponents through time-dependent Monte Carlo simulations. We use a method proposed recently to locate the nonequilibrium second-order phase transitions and that has been successfully used in systems with defined Hamiltonians and with absorbing states. This method, which is based on optimization of the coefficient of determination of the order parameter, was able to characterize the continuous phase transition of the model, as well as its upper spinodal point, a pseudocritical point located near the discontinuous phase transition. The static critical exponents $\beta , {\nu }_{\parallel }$, and ${\nu }_{\perp }$, as well as the dynamic critical exponents $\theta$ and $z$ for the continuous transition point, were also estimated and are in excellent agreement with results found in literature.

Raman scattering experiments on LaFeAsO with distinct antiferromagnetic ($T_{\text{AFM}}=140$ K) and tetragonal-orthorhombic ($T_S=155$ K) transitions show a quasielastic peak (QEP) in $B_{2g}$ symmetry (2 Fe tetragonal cell) that fades away below $\sim T_{\text{AFM}}$ and is ascribed to electronic nematic fluctuations. A scaling of the reported shear modulus with the $T$ dependence of the QEP height rather than the QEP area indicates that magnetic degrees of freedom drive the structural transition. The large separation between $T_S$ and $T_{\text{AFM}}$ in LaFeAsO compared to ${\mathrm{BaFe}}_2{\mathrm{As}}_2$ manifests itself in slower dynamics of nematic fluctuations in the former.