Stochastic Models of Learning

  title={Stochastic Models of Learning},
  author={Dirk Ifenthaler and Norbert M. Seel},
A model of discrete choice based on reinforcement learning under short-term memory
A parametric model of choice based on the probability maximization principle is proposed, as a model for deviations from expected utility principle, and is applied to the classical problem of demand for insurance. Expand
Reinforcement Learning for Repeated Power Control Game in Cognitive Radio Networks
This research provides the solution for the first time for the incomplete-information power control game in CR networks through reinforcement learning, which does not require the interference channel and power strategy information among CR users (and from CR users to PUs). Expand
Advancing Learning and Evolutionary Game Theory
This thesis advances game theory by formally analysing the implications of some of its most stringent assumptions and suggests that some of the most fundamental assumptions embedded in game theory may have deeper philosophical implications than commonly assumed. Expand
On the Existence and Uniqueness of the Solution of a Probabilistic Functional Equation Approached by the Banach Fixed Point Theorem
This paper deals with a particular class of probabilistic functional equations used to observe animals’ psychological learning process. Our aims are to find the existence and uniqueness of suchExpand
Learning in Repeated Public Goods Games - A Meta Analysis
I examine the generalizability of a broad range of prominent learning models in explaining contribution patterns in repeated linear public goods games. Experimental data from twelve previouslyExpand
Artificial Intelligence: A Child’s Play
Abstract We discuss the objectives of any endeavor in creating artificial intelligence, AI, and provide a possible alternative. Intelligence might be an unintended consequence of curiosity left toExpand
Bias in Semantic and Discourse Interpretation
It is shown how game-theoretic work on conversation combined with a theory of discourse structure provides a framework for studying interpretive bias and the factors that contribute to them. Expand
Big Fish Vs. Big Pond? Entrepreneurs, Established Firms, and Antecedents of Tie Formation
Entrepreneurial and established firms form collaborative relationships to commercialize products. Through such ties, entrepreneurs seek (1) development help to hone ideas into marketable products a...
Decision-making: from neuroscience to neuroeconomics—an overview
By the late 1990s, several converging trends in economics, psychology, and neuroscience had set the stage for the birth of a new scientific field known as “neuroeconomics”. Without the availabilityExpand
Existence, Uniqueness, and Stability Analysis of the Probabilistic Functional Equation Emerging in Mathematical Biology and the Theory of Learning
A generic probabilistic functional equation is proposed that can cover most of the mathematical models addressed in the existing literature and is utilized to examine the existence, uniqueness, and stability of the suggested equation’s solution. Expand


A longitudinal perspective on inductive reasoning tasks. Illuminating the probability of change
Abstract Cognitive scientists have studied internal cognitive structures, processes, and systems for decades in order to understand how they function in human learning. Nevertheless, questionsExpand