The systematicity challenge to anti-representational dynamicism

After more than twenty years of representational debate in the cognitive sciences, anti-representational dynamicism may be seen as offering a rival and radically new kind of explanation of systematicity phenomena. In this paper, I argue that, on the contrary, anti-representational dynamicism must face a version of the old systematicity challenge: either it does not explain systematicity, or else, it is just an implementation of representational theories. To show this, I present a purely behavioral and representation-free account of systematicity. I then consider a case of insect sensorimotor systematic behavior: communicating behavior in honey bees. I conclude that anti-representational dynamicism fails to capture the fundamental trait of systematic behaviors qua systematic, i.e., their involving exercises of the same behavioral capacities. I suggest, finally, a collaborative strategy in pursuit of a rich and powerful account of this central phenomenon of high cognition at all levels of explanation, including the representational level

Mating dances and the evolution of language: What’s the next step?

The Darwinian protolanguage hypothesis is one of the most popular theories of the evolution of human language. According to this hypothesis, language evolved through a three stage process involving general increases in intelligence, the emergence of grammatical structure as a result of sexual selection on protomusical songs, and finally the attachment of meaning to the components of those songs. The strongest evidence for the second stage of this process has been considered to be birdsong, and as a result researchers have investigated the existence of various forms of grammar in the production and comprehension of songs by birds. Here, we argue that mating dances are another relevant source of sexually-selected complexity that has until now been largely overlooked by proponents of Darwinian protolanguage, focusing especially on the dances of long-tailed manakins. We end by sketching several lines of research that should be pursued to determine the relevance of mating dances to the evolution of language

Bayesian reverse-engineering considered as a research strategy for cognitive science

Bayesian reverse-engineering is a research strategy for developing three-level explanations of behavior and cognition. Starting from a computational-level analysis of behavior and cognition as optimal probabilistic inference, Bayesian reverse-engineers apply numerous tweaks and heuristics to formulate testable hypotheses at the algorithmic and implementational levels. In so doing, they exploit recent technological advances in Bayesian artificial intelligence, machine learning, and statistics, but also consider established principles from cognitive psychology and neuroscience. Although these tweaks and heuristics are highly pragmatic in character and are often deployed unsystematically, Bayesian reverse-engineering avoids several important worries that have been raised about the explanatory credentials of Bayesian cognitive science: the worry that the lower levels of analysis are being ignored altogether; the challenge that the mathematical models being developed are unfalsifiable; and the charge that the terms optimal and rational have lost their customary normative force. But while Bayesian reverse-engineering is therefore a viable and productive research strategy, it is also no fool-proof recipe for explanatory success

Bayesian reverse-engineering considered as a research strategy for cognitive science

Bayesian reverse-engineering is a research strategy for developing three-level explanations of behavior and cognition. Starting from a computational-level analysis of behavior and cognition as optimal probabilistic inference, Bayesian reverse-engineers apply numerous tweaks and heuristics to formulate testable hypotheses at the algorithmic and implementational levels. In so doing, they exploit recent technological advances in Bayesian artificial intelligence, machine learning, and statistics, but also consider established principles from cognitive psychology and neuroscience. Although these tweaks and heuristics are highly pragmatic in character and are often deployed unsystematically, Bayesian reverse-engineering avoids several important worries that have been raised about the explanatory credentials of Bayesian cognitive science: the worry that the lower levels of analysis are being ignored altogether; the challenge that the mathematical models being developed are unfalsifiable; and the charge that the terms optimal and rational have lost their customary normative force. But while Bayesian reverse-engineering is therefore a viable and productive research strategy, it is also no fool-proof recipe for explanatory success

SciDAC's Earth System Grid Center for Enabling Technologies Semi-Annual Progress Report for the Period October 1, 2009 through March 31, 2010

This report summarizes work carried out by the ESG-CET during the period October 1, 2009 through March 31, 2009. It includes discussion of highlights, overall progress, period goals, collaborations, papers, and presentations. To learn more about our project, and to find previous reports, please visit the Earth System Grid Center for Enabling Technologies (ESG-CET) website. This report will be forwarded to the DOE SciDAC program management, the Office of Biological and Environmental Research (OBER) program management, national and international collaborators and stakeholders (e.g., the Community Climate System Model (CCSM), the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5), the Climate Science Computational End Station (CCES), the SciDAC II: A Scalable and Extensible Earth System Model for Climate Change Science, the North American Regional Climate Change Assessment Program (NARCCAP), and other wide-ranging climate model evaluation activities)

The structure and reproduction of the virgin forest - a review of Eustace Jones 1945

Jones (1945) was a milestone paper exploring the natural forest concept with examples from the temperate and boreal ecosystems. It has become a classic because of its use of field observation of regeneration, succession and structure to assess theories about disturbance and the dynamic properties of natural forests. His main aim was to review some of the features of the structure and reproduction of the north temperate virgin forests, and this article presents, discusses and evaluates the main features of this legendary paper. Jones had international experience of both the ecological and silvicultural research communities and combined long-term field observations with theory to develop a realistic assessment of natural forest properties that formed the basis for current understanding. He demonstrated that natural disturbance regimes could generate a variety of structures and that a stable, ‘‘climax’’ forest concept was often not supported by field data. He also showed that even-aged components are common in these forest ecosystems and that the recruitment of tree species proceeds irregularly even in undisturbed stands. His work has influenced subsequent development of related subjects such as disturbance theory, gap-phase dynamics and long-term vegetation changes and has left a legacy with practical relevance for nature conservation and silviculture