A Simple Artificial Life Model Explains Irrational Behavior in Human Decision-Making

Although praised for their rationality, humans often make poor decisions, even in simple situations. In the repeated binary choice experiment, an individual has to choose repeatedly between the same two alternatives, where a reward is assigned to one of them with fixed probability. The optimal strategy is to perseverate with choosing the alternative with the best expected return. Whereas many species perseverate, humans tend to match the frequencies of their choices to the frequencies of the alternatives, a sub-optimal strategy known as probability matching. Our goal was to find the primary cognitive constraints under which a set of simple evolutionary rules can lead to such contrasting behaviors. We simulated the evolution of artificial populations, wherein the fitness of each animat (artificial animal) depended on its ability to predict the next element of a sequence made up of a repeating binary string of varying size. When the string was short relative to the animats' neural capacity, they could learn it and correctly predict the next element of the sequence. When it was long, they could not learn it, turning to the next best option: to perseverate. Animats from the last generation then performed the task of predicting the next element of a non-periodical binary sequence. We found that, whereas animats with smaller neural capacity kept perseverating with the best alternative as before, animats with larger neural capacity, which had previously been able to learn the pattern of repeating strings, adopted probability matching, being outperformed by the perseverating animats. Our results demonstrate how the ability to make predictions in an environment endowed with regular patterns may lead to probability matching under less structured conditions. They point to probability matching as a likely by-product of adaptive cognitive strategies that were crucial in human evolution, but may lead to sub-optimal performances in other environments.

New insights on reaction pathway selectivity promoted by crown ether phase-transfer catalysis: Model ab initio calculations of nucleophilic fluorination

Crown ethers have the ability of solubilizing inorganic salts in apolar solvents and to promote chemical reactions by phase-transfer catalysis. However, details on how crown ethers catalyze ionic S(N)2 reactions and control selectivity are not well understood. In this work, we have used high level theoretical calculations to shed light on the details of phase-transfer catalysis mechanism of KF reaction with alkyl halides promoted by 18-crown-6. A complete analysis of the of the model reaction between KF(18-crown-6) and ethyl bromide reveals that the calculations can accurately predict the product ratio and the overall kinetics. Our results point out the importance of the K* ion and of the crown ether ring in determining product selectivity. While the K* ion favors the S(N)2 over the E2 anti pathway, the crown ether ring favors the S(N)2 over E2 syn route. The combination effects lead to a predicted 94% for the S(N)2 pathway in excellent agreement with the experimental value of 92%. A detailed analysis of the overall mechanism of the reaction under phase-transfer conditions also reveals that the KBr product generated in the nucleophilic fluorination acts as an inhibitor of the 18-crown-6 catalyst and it is responsible for the observed slow reaction rate. (C) 2012 Elsevier B.V. All rights reserved.

Photoisomerization for a model protonated Schiff base in solution: Sloped/peaked conical intersection perspective

The topographical character of conical intersections (CIs)-either sloped or peaked-has played a fundamental and important role in the discussion of the efficiency of CIs as photochemical "funnels." Here this perspective is employed in connection with a recent study of a model protonated Schiff base (PSB) cis to trans photoisomerization in solution [Malhado et al., J. Phys. Chem. A 115, 3720 (2011)]. In that study, the calculated reduced photochemical quantum yield for the successful production of trans product versus cis reactant in acetonitrile solvent compared to water was interpreted in terms of a dynamical solvent effect related to the dominance, for the acetonitrile case, of S-1 to S-0 nonadiabatic transitions prior to the reaching the seam of CIs. The solvent influence on the quantum yield is here re-examined in the sloped/peaked CI topographical perspective via conversion of the model's two PSB internal coordinates and a nonequilibrium solvent coordinate into an effective branching space description, which is then used to re-analyze the generalized Langevin equation/surface hopping results. The present study supports the original interpretation and enriches it in terms of topographical detail. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4754505]