Editors' Review and Introduction: Lying in Logic, Language, and Cognition.

We describe some recent trends in research on lying from a multidisciplinary perspective, including logic, philosophy, linguistics, psychology, cognitive science, behavioral economics, and artificial intelligence. Furthermore, we outline the seven contributions to this special issue of topiCS.

Accelerating the Development of Second-Order False Belief Reasoning: A Training Study With Different Feedback Methods.

One-hundred-six 5-year-olds' (Mage  = 5;6; SD = 0.40) were trained with second-order false belief tasks in one of the following conditions: (a) feedback with explanation; (b) feedback without explanation; (c) no feedback; (d) active control. The results showed that there were significant improvements in children's scores from pretest to posttest in the three experimental conditions even when children's age, verbal abilities, or working memory scores were controlled for. The training effect was stable at a follow-up session 4 months after the pretest. Overall, our results suggest that 5-year-olds' failures in second-order false belief tasks are due to lack of experience and that they can be helped over the threshold by exposure to many stories involving second-order false belief reasoning, including why questions.

Five-Year-Olds' Systematic Errors in Second-Order False Belief Tasks Are Due to First-Order Theory of Mind Strategy Selection: A Computational Modeling Study.

The focus of studies on second-order false belief reasoning generally was on investigating the roles of executive functions and language with correlational studies. Different from those studies, we focus on the question how 5-year-olds select and revise reasoning strategies in second-order false belief tasks by constructing two computational cognitive models of this process: an instance-based learning model and a reinforcement learning model. Unlike the reinforcement learning model, the instance-based learning model predicted that children who fail second-order false belief tasks would give answers based on first-order theory of mind (ToM) reasoning as opposed to zero-order reasoning. This prediction was confirmed with an empirical study that we conducted with 72 5- to 6-year-old children. The results showed that 17% of the answers were correct and 83% of the answers were wrong. In line with our prediction, 65% of the wrong answers were based on a first-order ToM strategy, while only 29% of them were based on a zero-order strategy (the remaining 6% of subjects did not provide any answer). Based on our instance-based learning model, we propose that when children get feedback "Wrong," they explicitly revise their strategy to a higher level instead of implicitly selecting one of the available ToM strategies. Moreover, we predict that children's failures are due to lack of experience and that with exposure to second-order false belief reasoning, children can revise their wrong first-order reasoning strategy to a correct second-order reasoning strategy.

Syntactic Recursion Facilitates and Working Memory Predicts Recursive Theory of Mind.

In this study, we focus on the possible roles of second-order syntactic recursion and working memory in terms of simple and complex span tasks in the development of second-order false belief reasoning. We tested 89 Turkish children in two age groups, one younger (4;6-6;5 years) and one older (6;7-8;10 years). Although second-order syntactic recursion is significantly correlated with the second-order false belief task, results of ordinal logistic regressions revealed that the main predictor of second-order false belief reasoning is complex working memory span. Unlike simple working memory and second-order syntactic recursion tasks, the complex working memory task required processing information serially with additional reasoning demands that require complex working memory strategies. Based on our results, we propose that children's second-order theory of mind develops when they have efficient reasoning rules to process embedded beliefs serially, thus overcoming a possible serial processing bottleneck.

The evolution of different forms of sociality: behavioral mechanisms and eco-evolutionary feedback.

Different forms of sociality have evolved via unique evolutionary trajectories. However, it remains unknown to what extent trajectories of social evolution depend on the specific characteristics of different species. Our approach to studying such trajectories is to use evolutionary case-studies, so that we can investigate how grouping co-evolves with a multitude of individual characteristics. Here we focus on anti-predator vigilance and foraging. We use an individual-based model, where behavioral mechanisms are specified, and costs and benefits are not predefined. We show that evolutionary changes in grouping alter selection pressures on vigilance, and vice versa. This eco-evolutionary feedback generates an evolutionary progression from "leader-follower" societies to "fission-fusion" societies, where cooperative vigilance in groups is maintained via a balance between within- and between-group selection. Group-level selection is generated from an assortment that arises spontaneously when vigilant and non-vigilant foragers have different grouping tendencies. The evolutionary maintenance of small groups, and cooperative vigilance in those groups, is therefore achieved simultaneously. The evolutionary phases, and the transitions between them, depend strongly on behavioral mechanisms. Thus, integrating behavioral mechanisms and eco-evolutionary feedback is critical for understanding what kinds of intermediate stages are involved during the evolution of particular forms of sociality.

A novel mechanism for a survival advantage of vigilant individuals in groups.

In many animal species, vigilance is crucial for avoiding predation. In groups, however, nonvigilant individuals could benefit from the vigilance of others without any of the associated costs. In an evolutionary sense, such exploitation may be compensated if vigilant individuals have a survival advantage. The novelty in our model is that the probability to detect a predator is "distance dependent." We show that even if nonvigilant individuals benefit fully from information produced by vigilant individuals, vigilant individuals nevertheless enjoy a survival advantage. This happens because detection of predators is more likely when vigilant individuals happen to be targets of predation. We expect this distance-dependent mechanism to be compatible with previously reported mechanisms.

What eye movements can tell about theory of mind in a strategic game.

This study investigates strategies in reasoning about mental states of others, a process that requires theory of mind. It is a first step in studying the cognitive basis of such reasoning, as strategies affect tradeoffs between cognitive resources. Participants were presented with a two-player game that required reasoning about the mental states of the opponent. Game theory literature discerns two candidate strategies that participants could use in this game: either forward reasoning or backward reasoning. Forward reasoning proceeds from the first decision point to the last, whereas backward reasoning proceeds in the opposite direction. Backward reasoning is the only optimal strategy, because the optimal outcome is known at each decision point. Nevertheless, we argue that participants prefer forward reasoning because it is similar to causal reasoning. Causal reasoning, in turn, is prevalent in human reasoning. Eye movements were measured to discern between forward and backward progressions of fixations. The observed fixation sequences corresponded best with forward reasoning. Early in games, the probability of observing a forward progression of fixations is higher than the probability of observing a backward progression. Later in games, the probabilities of forward and backward progressions are similar, which seems to imply that participants were either applying backward reasoning or jumping back to previous decision points while applying forward reasoning. Thus, the game-theoretical favorite strategy, backward reasoning, does seem to exist in human reasoning. However, participants preferred the more familiar, practiced, and prevalent strategy: forward reasoning.

Corvid re-caching without 'theory of mind': a model.

Scrub jays are thought to use many tactics to protect their caches. For instance, they predominantly bury food far away from conspecifics, and if they must cache while being watched, they often re-cache their worms later, once they are in private. Two explanations have been offered for such observations, and they are intensely debated. First, the birds may reason about their competitors' mental states, with a 'theory of mind'; alternatively, they may apply behavioral rules learned in daily life. Although this second hypothesis is cognitively simpler, it does seem to require a different, ad-hoc behavioral rule for every caching and re-caching pattern exhibited by the birds. Our new theory avoids this drawback by explaining a large variety of patterns as side-effects of stress and the resulting memory errors. Inspired by experimental data, we assume that re-caching is not motivated by a deliberate effort to safeguard specific caches from theft, but by a general desire to cache more. This desire is brought on by stress, which is determined by the presence and dominance of onlookers, and by unsuccessful recovery attempts. We study this theory in two experiments similar to those done with real birds with a kind of 'virtual bird', whose behavior depends on a set of basic assumptions about corvid cognition, and a well-established model of human memory. Our results show that the 'virtual bird' acts as the real birds did; its re-caching reflects whether it has been watched, how dominant its onlooker was, and how close to that onlooker it has cached. This happens even though it cannot attribute mental states, and it has only a single behavioral rule assumed to be previously learned. Thus, our simulations indicate that corvid re-caching can be explained without sophisticated social cognition. Given our specific predictions, our theory can easily be tested empirically.

Evolution of altruistic punishment in heterogeneous populations.

Evolutionary models for altruistic behavior typically make the assumption of homogeneity: each individual has the same costs and benefits associated with cooperating with each other and punishing for selfish behavior. In this paper, we relax this assumption by separating the population into heterogeneous classes, such that individuals from different classes differ in their ability to punish for selfishness. We compare the effects of introducing heterogeneity this way across two population models, that each represents a different type of population: the infinite and well-mixed population describes the way workers of social insects such as ants are organized, while a spatially structured population is more related to the way social norms evolve and are maintained in a social network. We find that heterogeneity in the effectiveness of punishment by itself has little to no effect on whether or not altruistic behavior will stabilize in a population. In contrast, heterogeneity in the cost that individuals pay to punish for selfish behavior allows altruistic behavior to be maintained more easily. Fewer punishers are needed to deter selfish behavior, and the individuals that punish will mostly belong to the class that pays a lower cost to do so. This effect is amplified when individuals that pay a lower cost for punishing inflict a higher punishment. The two population models differ when individuals that pay a low cost for punishing also inflict a lower punishment. In this situation, altruistic behavior becomes harder to maintain in an infinite and well-mixed population. However, this effect does not occur when the population is spatially structured.

Corvid caching: Insights from a cognitive model.

Caching and recovery of food by corvids is well-studied, but some ambiguous results remain. To help clarify these, we built a computational cognitive model. It is inspired by similar models built for humans, and it assumes that memory strength depends on frequency and recency of use. We compared our model's behavior to that of real birds in previously published experiments. Our model successfully replicated the outcomes of two experiments on recovery behavior and two experiments on cache site choice. Our "virtual birds" reproduced declines in recovery accuracy across sessions, revisits to previously emptied cache sites, a lack of correlation between caching and recovery order, and a preference for caching in safe locations. The model also produced two new explanations. First, that Clark's nutcrackers may become less accurate as recovery progresses not because of differential memory for different cache sites, as was once assumed, but because of chance effects. And second, that Western scrub jays may choose their cache sites not on the basis of negative recovery experiences only, as was previously thought, but on the basis of positive recovery experiences instead. Alternatively, both "punishment" and "reward" may be playing a role. We conclude with a set of new insights, a testable prediction, and directions for future work.