The give-or-take-some dilemma: An empirical investigation of a hybrid social dilemma

We describe and empirically investigate a hybrid social dilemma that merges give-some and take-some dilemmas by allowing individuals to choose to either give or to take resources from a shared resource pool. Study 1 finds that (a) group size increases the inequality among group members and the likelihood of creating the public good, while reducing the amount of wasted resources; (b) larger bonuses increase provision rates; and (c) asymmetry in the wealth distribution of the group members induces higher levels of inequality of the final outcomes. Following the logic of appropriateness, players with high (low) endowments were more likely to give toward (take from) the shared resource. Study 2 finds that the tendency of the players with high (low) endowments to give (take) is amplified as the difference between endowment levels increased, and the players’ behavior is correlated with, and predictable from, independent judgments of what is perceived as appropriate.     

Rectifying the Mischaracterization of Logic by Mental Model Theorists

Khemlani et al. (2018) mischaracterize logic in the course of seeking to show that mental model theory (MMT) can accommodate a form of inference (, let us label it) they find in a high percentage of their subjects. We reveal their mischaracterization and, in so doing, lay a landscape for future modeling by cognitive scientists who may wonder whether human reasoning is consistent with, or perhaps even capturable by, reasoning in a logic or family thereof. Along the way, we note that the properties touted by Khemlani et al. as innovative aspects of MMT-based modeling (e.g., nonmonotonicity) have for decades been, in logic, acknowledged and rigorously specified by families of (implemented) logics. Khemlani et al. (2018) further declare that is “invalid in any modal logic.” We demonstrate this to be false by our introduction (Appendix A) of a new propositional modal logic (within a family of such logics) in which is provably valid, and by the implementation of this logic. A second appendix, B, partially answers the two-part question, “What is a formal logic, and what is it for one to capture empirical phenomena?”     

Modeling the emergence of informational content by adaptive networks for temporal factorisation and criterial causation

Propagated activation of neurons through their network is an important process in the brain. Another crucial part of neural processing concerns adaptation over time of characteristics of this network such as connection strengths or excitability thresholds. This adaptation can be slow, as in learning from a multiple experiences, or it can be fast, as in memory formation. These adaptive network characteristics can be considered informational criteria for activation of a neuron. This then is viewed as a form of emergent information formation. Activation of neurons is determined by such information via a process termed criterial causation. In the current paper, the relationship of criterial causation with the principle of temporal factorisation for the dynamics of the world in general is explored. Temporal factorisation describes how the world represents information about its past in its present state, which then in turn determines the world’s future. In the paper, it is shown how these processes are analysed in more detail and modeled by (adaptive) network models.