Reinforcement learning (RL) agents have been deployed in complex environments where interactions are costly, and learning is usually slow. One prominent task in these settings is to reuse interactions performed by other agents to accelerate the learning process. Causal inference provides a family of methods to infer the effects of actions from a combination of data and qualitative assumptions a...

a neuro-fuzzy modeling tool (anfis) has been used to dynamically model cross flow ultrafiltration of milk. it aims to predict permeate flux and total hydraulic resistance as a function of transmembrane pressure, ph, temperature, fat, molecular weight cut off, and processing time. dynamic modeling of ultrafiltration performance of colloidal systems (such as milk) is very important for designing ...

there are different strategies for selecting stocks, and different investors use different strategies according to their risk tolerance or their expected rate of return. in this study, the profitability of a broad range of stock se-lection strategies in tehran stock exchange over the period 1370-1383, has been examined, and it has been investigated whether the successful strategies in other cou...

To maximize clinical benefit, clinicians routinely tailor treatment to the individual characteristics of each patient, where individualized rules are needed and significant research interest statisticians. In covariate-adjusted randomization trial with many covariates, we model effect an unspecified function a single index covariates leave baseline response completely arbitrary. We devise class...

The inference of correlated signal fields with unknown correlation structures is of high scientific and technological relevance, but poses significant conceptual and numerical challenges. To address these, we develop the correlated signal inference (CSI) algorithm within information field theory (IFT) and discuss its numerical implementation. To this end, we introduce the free energy exploratio...

Our paper deals with inferring simulator-based statistical models given some observed data. A simulator-based model is a parametrized mechanism which specifies how data are generated. It is thus also referred to as generative model. We assume that only a finite number of parameters are of interest and allow the generative process to be very general; it may be a noisy nonlinear dynamical system ...

Learning about ecosystem processes and patterns is an essential component of Ecosystem Based Fishery Management and the sustainable use of natural resources. Currently, such learning is usually done through adaptive management (passive or active) or Management Strategy Evaluation, which are explained. An example of adaptive management in northwestern Australia shows the strengths and limitation...