A Formal Separation Between Strategic and Nonstrategic Behavior

It is common in multiagent systems to make a distinction between "strategic" behavior and other forms of intentional but "nonstrategic" behavior: typically, that strategic agents model other agents while nonstrategic agents do not. However, a crisp boundary between these concepts has proven elusive. This problem is pervasive throughout the game theoretic literature on bounded rationality and particularly critical in parts of the behavioral game theory literature that make an explicit distinction between the behavior of "nonstrategic" level-0 agents and "strategic" higher-level agents (e.g., the level-k and cognitive hierarchy models). Overall, work discussing bounded rationality rarely gives clear guidance on how the rationality of nonstrategic agents must be bounded, instead typically just singling out specific decision rules and informally asserting them to be nonstrategic (e.g., truthfully revealing private information; randomizing uniformly). In this work, we propose a new, formal characterization of nonstrategic behavior. Our main contribution is to show that it satisfies two properties: (1) it is general enough to capture all purportedly "nonstrategic" decision rules of which we are aware in the behavioral game theory literature; (2) behavior that obeys our characterization is distinct from strategic behavior in a precise sense

DETERMINANTS OF CONSUMER ATTITUDES AND PURCHASE INTENTIONS WITH REGARD TO GM FOODS

Consumer acceptance of genetically modified (GM) products has become a vital factor in determining how prosperous the markets for GM products will be in the future. This phenomenon creates increased interest in understanding consumer attitudes and purchase intentions with regard to GM foods. Thus, this paper presents results based on a contingent valuation questionnaire designed to assess consumer knowledge, awareness and willingness to purchase GM-tomatoes in Huntsville metropolitan area, Alabama. The results suggest that attitudes and purchase decisions concerning GM foods are generally negative, highly complex and are based on several factors.Consumer/Household Economics,

Learning in the Repeated Secretary Problem

In the classical secretary problem, one attempts to find the maximum of an unknown and unlearnable distribution through sequential search. In many real-world searches, however, distributions are not entirely unknown and can be learned through experience. To investigate learning in such a repeated secretary problem we conduct a large-scale behavioral experiment in which people search repeatedly from fixed distributions. In contrast to prior investigations that find no evidence for learning in the classical scenario, in the repeated setting we observe substantial learning resulting in near-optimal stopping behavior. We conduct a Bayesian comparison of multiple behavioral models which shows that participants' behavior is best described by a class of threshold-based models that contains the theoretically optimal strategy. Fitting such a threshold-based model to data reveals players' estimated thresholds to be surprisingly close to the optimal thresholds after only a small number of games

DETERMINING THE EFFECTS OF LAND CHARACTERISTICS ON FARMLAND VALUES IN SOUTH-CENTRAL IDAHO

This study focused on evaluating the effects of different attributes that impact irrigated farmland values in South-central Idaho. Results indicate that study area farmland values are largely determined by agricultural productivity (profiability) related factors. However, estimated "development increment values" for parcels that seemed to be under development pressure in the study area are explainable by nonagricultural variables.Land Economics/Use,

Guarantees for Self-Play in Multiplayer Games via Polymatrix Decomposability

Self-play is a technique for machine learning in multi-agent systems where a learning algorithm learns by interacting with copies of itself. Self-play is useful for generating large quantities of data for learning, but has the drawback that the agents the learner will face post-training may have dramatically different behavior than the learner came to expect by interacting with itself. For the special case of two-player constant-sum games, self-play that reaches Nash equilibrium is guaranteed to produce strategies that perform well against any post-training opponent; however, no such guarantee exists for multiplayer games. We show that in games that approximately decompose into a set of two-player constant-sum games (called constant-sum polymatrix games) where global $\epsilon$-Nash equilibria are boundedly far from Nash equilibria in each subgame (called subgame stability), any no-external-regret algorithm that learns by self-play will produce a strategy with bounded vulnerability. For the first time, our results identify a structural property of multiplayer games that enable performance guarantees for the strategies produced by a broad class of self-play algorithms. We demonstrate our findings through experiments on Leduc poker.Comment: To appear at NeurIPS 202

Neutrinos from type Ia supernovae: the deflagration-to-detonation transition scenario

It has long been recognized that the neutrinos detected from the next core-collapse supernova in the Galaxy have the potential to reveal important information about the dynamics of the explosion and the nucleosynthesis conditions as well as allowing us to probe the properties of the neutrino itself. The neutrinos emitted from thermonuclear - type Ia - supernovae also possess the same potential, although these supernovae are dimmer neutrino sources. For the first time, we calculate the time, energy, line of sight, and neutrino-flavor-dependent features of the neutrino signal expected from a three-dimensional delayed-detonation explosion simulation, where a deflagration-to-detonation transition triggers the complete disruption of a near-Chandrasekhar mass carbon-oxygen white dwarf. We also calculate the neutrino flavor evolution along eight lines of sight through the simulation as a function of time and energy using an exact three-flavor transformation code. We identify a characteristic spectral peak at $\sim 10$ MeV as a signature of electron captures on copper. This peak is a potentially distinguishing feature of explosion models since it reflects the nucleosynthesis conditions early in the explosion. We simulate the event rates in the Super-K, Hyper-K, JUNO, and DUNE neutrino detectors with the SNOwGLoBES event rate calculation software and also compute the IceCube signal. Hyper-K will be able to detect neutrinos from our model out to a distance of $\sim 10$ kpc. At 1 kpc, JUNO, Super-K, and DUNE would register a few events while IceCube and Hyper-K would register several tens of events.Comment: 44 pages, 29 figures & 2 tables. Updated to match Phys. Rev. D version, including a new event channel discussion and improved IceCube result

Infrared images of merging galaxies

Infrared imaging of interacting galaxies is especially interesting because their optical appearance is often so chaotic due to extinction by dust and emission from star formation regions, that it is impossible to locate the nuclei or determine the true stellar distribution. However, at near-infrared wavelengths extinction is considerably reduced, and most of the flux from galaxies originates from red giant stars that comprise the dominant stellar component by mass. Thus near infrared images offer the opportunity to study directly components of galactic structure which are otherwise inaccessible. Such images may ultimately provide the framework in which to understand the activity taking place in many of the mergers with high Infrared Astronomy Satellite (IRAS) luminosities. Infrared images have been useful in identifying double structures in the nuclei of interacting galaxies which have not even been hinted at by optical observations. A striking example of this is given by the K images of Arp 220. Graham et al. (1990) have used high resolution imaging to show that it has a double nucleus coincident with the radio sources in the middle of the dust lane. The results suggest that caution should be applied in the identification of optical bright spots as multiple nuclei in the absence of other evidence. They also illustrate the advantages of using infrared imaging to study the underlying structure in merging galaxies. The authors have begun a program to take near infrared images of galaxies which are believed to be mergers of disk galaxies because they have tidal tails and filaments. In many of these the merger is thought to have induced exceptionally luminous infrared emission (cf. Joseph and Wright 1985, Sanders et al. 1988). Although the optical images of the galaxies show spectacular dust lanes and filaments, the K images all have a very smooth distribution of light with an apparently single nucleus