The Truth is in the Eye of the Beholder: or Equilibrium in Beliefs and Rational Learning in Games

Games with incomplete information or randomness in the moves of others typically have many decision-theoretically equivalent formulations of the type space. These different formulations correspond to different ways of encoding tha realizations of randomizations in the type of a player. Solution concepts, assumptions or paradoxes in games should be independent of the formulation of the game used. I refer to this axiom as TIGER, for "Type Independence among Games which are equivalently Re-formulated".GAMES ; LEARNING

Learning, Quantal Response Equilibrium and Equilibrium in Beliefs

This paper makes two points. First, the modeling used in the rational (or Bayesian) learning literature can be generalized to handle the repeated shocks to preferences inherent and implicit in models of quantal response equilibria (QRE). In particular, we note that the Bayesian model and the QRE model are really not as different as often portrayed in the literature. Second, Bayesian learning under appropriate conditions therefore leads to a QRE.QUANTAL RESPONSE EQUILIBRIUM; BAYESIAN LEARNING; GAME THEORY

The "Types" of a Baysian Equilibrium

economic equilibrium ; information

The Savage-Bayesian Foundations of Economic Dynamics

information ; economic equilibrium

Bayesian Learning without Common Priors and Convergence to Nash Equilibria

economic equilibrium ; economic models ; game theory

Learning and agreeing to disagree without common priors.

Market ; games ; economic information

Bayesian Learning in Repeated Games Leads to Correlated Equilibria

game theory ; economic models

Heavy Metal Loading in Surface Sediments along the Kawere Stream, Tarkwa, Ghana

Sediment contamination by heavy metals resulting from anthropogenic activities is increasingly becoming a global concern due to the risk it poses to human well-being and ecological integrity at large. The purpose of this study was to assess the heavy metals loading in sediment along the Kawere stream. Ten sediment samples were collected, acid digested and analysed for copper (Cu), lead (Pb), cadmium (Cd), manganese (Mn), zinc (Zn), nickel (Ni), chromium (Cr), cobalt (Co) and iron (Fe) using a Varian AA240FS Atomic Absorption Spectrometer (AAS). The Australian and New Zealand Environment and Conservation Council (ANZECC) guidelines for freshwater sediment quality was used as the benchmark against which the measured metal concentrations were compared. Nemerow’s pollution and potential ecological risk indices were used to evaluate the pollution status and ecological risk levels of the heavy metals in the stream. The results obtained indicated that, except Cu which exceeded the ANZECC trigger value of 65 mg/kg at three sampling sites (K01=171.29 mg/kg, K05=170.83 mg/kg and K07=113.31 mg/kg), all other measured heavy metals concentrations were below their corresponding ANZECC values. Heavy metal pollution assessment showed that three samples (K01, K05 and K07) were slightly polluted, suggesting the likelihood of posing a health threat to the aquatic organisms and humans. Calculated Ecological Risk Index (RI) ranged from 3.229 to 19.750 (RI < 150), representing a low ecological risk. As such, the metals, Cu, Ni, Cd, Pb, Cr, and Zn pose a low ecological risk to the aquatic ecosystem. Although the ecological risk is low based on the current results, constant monitoring of the stream quality is recommended due to the increasing human activities along the stream as well as the sediments ability to accumulate and remobilise heavy metals back into the water column and possibly transferring them through the food chain.   Keywords: Heavy Metals, Sediment, Ecological Risk Assessment, Pollution, Strea

Learning by Doing and the Choice of Technology.

This a one-agent model of learning by doing and technology choice. The more the agent uses a technology, the better he learns its parameters, and the more productive he gets. This expertise is a form of human capital.TECHNOLOGY;TRAINING

Research and Productivity.

We model research as a signal on an unknown parameter of a technology.PRODUCTIVITY;RESEARCH AND DEVELOPMENT