Building Machines That Learn and Think Like People

Recent progress in artificial intelligence (AI) has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn, and how they learn it. Specifically, we argue that these machines should (a) build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; (b) ground learning in intuitive theories of physics and psychology, to support and enrich the knowledge that is learned; and (c) harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes towards these goals that can combine the strengths of recent neural network advances with more structured cognitive models.Comment: In press at Behavioral and Brain Sciences. Open call for commentary proposals (until Nov. 22, 2016). https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/information/calls-for-commentary/open-calls-for-commentar

Baryogenesis from the Kobayashi-Maskawa Phase

The Standard Model fulfills the three Sakharov conditions for baryogenesis. The smallness of quark masses suppresses, however, the CP violation from the Kobayashi-Maskawa phase to a level that is many orders of magnitude below what is required to explain the observed baryon asymmetry. We point out that if, as a result of time variation in the Yukawa couplings, quark masses were large at the time of the electroweak phase transition, then the Kobayashi-Maskawa mechanism could be the source of the asymmetry. The Froggatt-Nielsen mechanism provides a plausible framework where the Yukawa couplings could all be of order one at that time, and settle to their present values before nucleosynthesis. The problems related to a strong first order electroweak phase transition may also be alleviated in this framework. Our scenario reveals a loophole in the commonly held view that the Kobayashi-Maskawa mechanism cannot be the dominant source of CP violation to play a role in baryogenesis.Comment: 4 page

SPECTRAL PROCEDURES ENHANCE THE ANALYSIS OF THREE AGRICULTURAL TIME SERIES

Many agricultural and environmental variables are influenced by cyclic processes that occur naturally. Consequently their time series often have cyclic behavior. This study develops time series models for three different phenomena: (1) a 60 year-long state annual average crop yield record, (2) a four year-long daily stream flow record with values aggregated to weekly averages, and (3) a half-hour long wind speed record sampled at 10 hertz with values aggregated to 0.5 min averages. Trend tests, simple high pass filtering, and spectral analysis on original and detrended and residual data series are used to guide model development. Next, as a means to provide insight for researchers, nonlinear regression procedures are used to develop models in the time domain. The models considered may have a large scale trend, low to high frequency cycles, and, if need be, an autoregressive (AR) error structure. Selected models for all three sets included a trend component. The model for yield has a linear trend in time and includes two high frequency cycles of 2.3 and 2.5 years. The model for stream flow has a complicated trend consisting of splined polynomials in the square root of time. Cycles include an annual and approximately 8, 6, and 3 month periods. Also an AR1 error structure is added. Results suggest the wind speed can be modeled as a superposition of damped and undamped oscillations. A zero order fractional Bessel function models the trend, here a damped oscillation with a period of 10.5 min. Smaller scale regular cycles of 6.6, 3.3 and 2.2 min are added along with an AR1 error structure. The use of time series methods instead of the inverse transform on selected frequencies allows for simultaneous estimation of all components. Moreover it opens the door to the use of a much broader class of functions to model the trend, to the use of other kinds of periodic functions to model the cycles, and to the incorporation of structure in the error term. This approach may provide useful insight and a methodological approach for several ongoing and some future studies at the National Soil Tilth Laboratory

Theme Overview: Agriculture and Water Quality in the Cornbelt: Overview of Issues and Approaches

Resource /Energy Economics and Policy, Q25,

Identifying Riparian Zones Best Suited to Installation of Saturated Buffers: A Preliminary Multi-Watershed Assessment

Saturated riparian buffers are a new type of conservation practice that divert subsurface tile drainage water from direct discharge to surface water into distribution pipes that discharge the tile water into riparian soils. This enables natural processes of biological uptake and denitrification to decrease nutrient loads that are being lost from croplands via tile drains, reducing water quality impacts from agriculture at relatively little cost. This chapter suggests and evaluates draft criteria that identify riparian zones within a watershed that are suited to installation of saturated buffers. Soils criteria, evaluated using soil survey information, include subsurface accumulations of soil organic matter (SOM) (\u3e 1% SOM at 0.75–1.2 m depth), relatively fine-textured subsoils (\u3c 50% sand at 0.75–1.2 m depth), and a shallow water table (\u3c 1 m depth) April through June. These criteria highlight riparian locations where soil conditions should enhance nutrient removal. Criteria are also proposed to avoid locations where streambank failure and/or inundation of crops adjacent to the buffer may occur, which are evaluated using high-resolution digital elevation models, now widely available through LiDAR (light detection and ranging) surveys. The criteria were evaluated in three Midwestern HUC-12 watersheds dominated by fine-grained glacial deposits. Results showed topographic criteria were more restrictive than soils criteria, especially in the flattest landscapes, but 30 to 60% of streambank lengths in the test watersheds were deemed suitable to installation of saturated buffers. This evaluation contributed to inclusion of a saturated buffer siting tool in the Agricultural Conservation Planning Framework (ACPF). Local information is needed to design this practice to fit site conditions

Separatrix Divergence of Stellar Streams in Galactic Potentials

Flattened axisymmetric galactic potentials are known to host minor orbit families surrounding orbits with commensurable frequencies. The behavior of orbits that belong to these orbit families is fundamentally different than that of typical orbits with non-commensurable frequencies. We investigate the evolution of stellar streams on orbits near the boundaries between orbit families (separatrices) in a flattened axisymmetric potential. We demonstrate that the separatrix divides these streams into two groups of stars that belong to two different orbit families, and that as a result, these streams diffuse more rapidly than streams that evolve elsewhere in the potential. We utilize Hamiltonian perturbation theory to estimate both the timescale of this effect and the likelihood of a stream evolving close enough to a separatrix to be affected by it. We analyze two prior reports of stream-fanning in simulations with triaxial potentials, and conclude that at least one of them is caused by separatrix divergence. These results lay the foundation for a method of mapping the orbit families of galactic potentials using the morphology of stellar streams. Comparing these predictions with the currently known distribution of streams in the Milky Way presents a new way of constraining the shape of our Galaxy's potential and distribution of dark matter.Comment: 12 pages, 7 figures. Accepted for publication in MNRA

A Tale of Three Watersheds: Nonpoint Source Pollution and Conservation Practices across Iowa

Resource /Energy Economics and Policy, Q25,

Brief Training to Modify the Breadth of Attention Influences the Generalisation of Fear

Background: Generalisation of fear from dangerous to safe stimuli is an important process associated with anxiety disorders. However, factors that contribute towards fear (over)-generalisation remain poorly understood. The present investigation explored how attentional breadth (global/holistic and local/analytic) influences fear generalisation and, whether people trained to attend in a global vs. local manner show more or less generalisation. Methods: Participants (N = 39) were shown stimuli which comprised of large ‘global’ letters and smaller ‘local’ letters (e.g. an F comprised of As) and they either had to identify the global or local letter. Participants were then conditioned to fear a face by pairing it with an aversive scream (75% reinforcement schedule). Perceptually similar, but safe, faces, were then shown. Self-reported fear levels and skin conductance responses were measured. Results: Compared to participants in Global group, participants in Local group demonstrated greater fear for dangerous stimulus (CS +) as well as perceptually similar safe stimuli. Conclusions: Participants trained to attend to stimuli in a local/analytical manner showed higher magnitude of fear acquisition and generalisation than participants trained to attend in a global/holistic way. Breadth of attentional focus can influence overall fear levels and fear generalisation and this can be manipulated via attentional training