The evolution and devolution of cognitive control : the costs of deliberation in a competitive world

Dual-system theories of human cognition, under which fast automatic processes can complement or compete with slower deliberative processes, have not typically been incorporated into larger scale population models used in evolutionary biology, macroeconomics, or sociology. However, doing so may reveal important phenomena at the population level. Here, we introduce a novel model of the evolution of dual-system agents using a resource-consumption paradigm. By simulating agents with the capacity for both automatic and controlled processing, we illustrate how controlled processing may not always be selected over rigid, but rapid, automatic processing. Furthermore, even when controlled processing is advantageous, frequency-dependent effects may exist whereby the spread of control within the population undermines this advantage. As a result, the level of controlled processing in the population can oscillate persistently, or even go extinct in the long run. Our model illustrates how dual-system psychology can be incorporated into population-level evolutionary models, and how such a framework can be used to examine the dynamics of interaction between automatic and controlled processing that transpire over an evolutionary time scale

Antibiotic resistance in the environment, with particular reference to MRSA

The introduction of β-lactam antibiotics (penicillins and cephalosporins) in the 1940s and 1950s probably represents the most dramatic event in the battle against infection in human medicine. Even before widespread global use of penicillin, resistance was already recorded. E. coli producing a penicillinase was reported in Nature in 1940 (Abraham, 1940) and soon after a similar penicillinase was discovered in Staphylococcus aureus (Kirby, 1944). The appearance of these genes, so quickly after the discovery and before the widespread introduction of penicillin, clearly shows that the resistance genes pre-dated clinical use of the antibiotic itself

UG Sim - Monotonic without selection (N = 200)

Ultimatum Game simulation dat

UG Sim - Responders constrained to accept only hyperfair offers (N = 100)

Ultimatum Game simulation dat

Data from: Rational constraints and the evolution of fairness in the Ultimatum Game

Behavior in the Ultimatum Game has been well-studied experimentally, and provides a marked contrast between the theoretical model of a self-interested economic agent and that of an actual human concerned with social norms such as fairness. How did such norms evolve, when punishing unfair behavior can be costly to the punishing agent? The work described here simulated a series of Ultimatum Games, in which populations of agents earned resources based on their preferences for proposing and accepting (or rejecting) offers of various sizes. Two different systems governing the acceptance or rejection of offers were implemented. Under one system, the probability that an agent accepted an offer of a given size was independent of the probabilities of accepting the other possible offers. Under the other system, a simple, ordinal constraint was placed on the acceptance probabilities such that a given offer was at least as likely to be accepted as a smaller offer. For simulations under either system, agents’ preferences and their corresponding behavior evolved over multiple generations. Populations without the ordinal constraint came to emulate maximizing economic agents, while populations with the constraint came to resemble the behavior of human players

Consensus Decision-Making: Performance of Heuristics and Mental Models

Consensus decision-making, found in settings ranging from formal institutions to ad hoc groups, represents a critical component of human social interaction. In such cases, decision-makers often must agree to a course of action with awareness of others\u27 behavior (e.g., votes) but not group members\u27 underlying motivations and strategies. How, then, should individual agents/decision-makers balance the payoffs of available options against the time it takes to reach consensus (ranging from quick consensus to stalemate)? In the current research, a novel, repeated consensus task was played by simulated agents. These agents differed in how they a) evaluated the available options and b) anticipated the choices of fellow group members. While intuition may suggest that intractably selfish agents will outcompete those willing to compromise, the data demonstrate that socially minded agents – i.e., one type that employed a simple heuristic and two types that employed sophisticated social cognition – were the only ones to exhibit evolutionarily stable strategies. However, sophisticated cognition did not guarantee good performance, suggesting that caution is warranted in trying to “outsmart” competing agents. While these agents were restricted to simple behaviors, the approach and models described here provide a potentially useful framework for studying consensus in humans

UG Sim - Both roles initialized to rational behavior (N = 100)

Ultimatum Game simulation dat

UG Sim - Roles separate and heritable (N = 100)

Ultimatum Game simulation dat

UG Sim - Monotonic with selection (N = 50)

Ultimatum Game simulation dat

UG Sim - Responders initialized to rational acceptance function (N = 100)

Ultimatum Game simulation dat