Social learning with coarse inference

We study social learning by boundedly rational agents. Agents take a decision in sequence, after observing their predecessors and a private signal. They are unable to understand their predecessors’ decisions in their finest details: they only understand the relation between the aggregate distribution of actions and the state of nature. We show that, in a continuous action space, compared to the rational case, agents put more weight on early signals. Despite this behavioral bias, beliefs converge to the truth. In a discrete action space, instead, convergence to the truth does not occur even if agents receive signals of unbounded precisions

Reification and Truthmaking Patterns

Reification is a standard technique in conceptual modeling, which consists of including in the domain of discourse entities that may otherwise be hidden or implicit. However, deciding what should be rei- fied is not always easy. Recent work on formal ontology offers us a simple answer: put in the domain of discourse those entities that are responsible for the (alleged) truth of our propositions. These are called truthmakers. Re-visiting previous work, we propose in this paper a systematic analysis of truthmaking patterns for properties and relations based on the ontolog- ical nature of their truthmakers. Truthmaking patterns will be presented as generalization of reification patterns, accounting for the fact that, in some cases, we do not reify a property or a relationship directly, but we rather reify its truthmakers

Paesaggi marginali e paesaggi mediati

L’evoluzione socio-economica ha radicalmente cambiato i paesaggi dell’europa, che erano stati plasmati dalle comunità rurali. Il recupero, con una valorizzazione economica e simbolica, è possibile solo con una nuova consapevolezza e responsabilità dell’intera società

Optimism and pessimism in strategic interactions under ignorance

We study players interacting under the veil of ignorance, who have—coarse—beliefs represented as subsets of opponents' actions. We analyze when these players follow max⁡min or max⁡max decision criteria, which we identify with pessimistic or optimistic attitudes, respectively. Explicitly formalizing these attitudes and how players reason interactively under ignorance, we characterize the behavioral implications related to common belief in these events: while optimism is related to Point Rationalizability, a new algorithm—Wald Rationalizability—captures pessimism. Our characterizations allow us to uncover novel results: (i) regarding optimism, we relate it to wishful thinking á la Yildiz (2007) and we prove that dropping the (implicit) “belief-implies-truth” assumption reverses an existence failure described therein; (ii) we shed light on the notion of rationality in ordinal games; (iii) we clarify the conceptual underpinnings behind a discontinuity in Rationalizability hinted in the analysis of Weinstein (2016)

Common priors under endogenous uncertainty

For a fixed game and a type structure that admits a common prior, Action Independence states that the conditional beliefs induced by the common prior do not depend on the players' own strategies. It has been conjectured that Action Independence can be behaviorally characterized by means of a suitable no-betting condition (Dekel and Siniscalchi, 2015), but whether this is indeed the case remains an open problem. In this paper, we prove this conjecture true by focusing on strategy-invariant bets, which are bets that cannot be manipulated by the players. In particular, first, we show that at least one of the common priors satisfies Action Independence if and only if there exists no mutually acceptable strategy-invariant bet among the players. Second, we show that, all common priors satisfy Action Independence if and only if there exists no mutually acceptable strategy-invariant bet among the players and an outside observer. These results give us a deeper understanding of existing foundations of solution concepts using only epistemic conditions that are expressed in terms of type structures and are therefore elicitable

Population Genetic Structure and Species Delimitation of a Widespread, Neotropical Dwarf Gecko

Amazonia harbors the greatest biological diversity on Earth. One trend that spans Amazonian taxa is that most taxonomic groups either exhibit broad geographic ranges or small restricted ranges. This is likely because many traits that determine a species range size, such as dispersal ability or body size, are autocorrelated. As such, it is rare to find groups that exhibit both large and small ranges. Once identified, however, these groups provide a powerful system for isolating specific traits that influence species distributions. One group of terrestrial vertebrates, gecko lizards, tends to exhibit small geographic ranges. Despite one exception, this applies to the Neotropical dwarf geckos of the genus Gonatodes. This exception, Gonatodes humeralis, has a geographic distribution almost 1,000,000 km2 larger than the combined ranges of its 30 congeners. As the smallest member of its genus and a gecko lizard more generally, G. humeralis is an unlikely candidate to be a wide-ranged Amazonian taxon. To test whether or not G. humeralis is one or more species, we generated molecular genetic data using restriction-site associated sequencing (RADseq) and traditional Sanger methods for samples from across its range and conducted a phylogeographic study. We conclude that G. humeralis is, in fact, a single species across its contiguous range in South America. Thus, Gonatodes is a unique clade among Neotropical taxa, containing both wide-ranged and range-restricted taxa, which provides empiricists with a powerful model system to correlate complex species traits and distributions. Additionally, we provide evidence to support species-level divergence of the allopatric population from Trinidad and we resurrect the name Gonatodes ferrugineus from synonymy for this population

Geographical information retrieval with ontologies of place

Geographical context is required of many information retrieval tasks in which the target of the search may be documents, images or records which are referenced to geographical space only by means of place names. Often there may be an imprecise match between the query name and the names associated with candidate sources of information. There is a need therefore for geographical information retrieval facilities that can rank the relevance of candidate information with respect to geographical closeness of place as well as semantic closeness with respect to the information of interest. Here we present an ontology of place that combines limited coordinate data with semantic and qualitative spatial relationships between places. This parsimonious model of geographical place supports maintenance of knowledge of place names that relate to extensive regions of the Earth at multiple levels of granularity. The ontology has been implemented with a semantic modelling system linking non-spatial conceptual hierarchies with the place ontology. An hierarchical spatial distance measure is combined with Euclidean distance between place centroids to create a hybrid spatial distance measure. This is integrated with thematic distance, based on classification semantics, to create an integrated semantic closeness measure that can be used for a relevance ranking of retrieved objects