This chapter introduces readers to the broader network of strategies to which action learning may be considered an important hub. For very pragmatic purposes, action learning, according to the author, needs to link with its natural cousins, referred to as ‘action modalities.’ After providing...

Parliamentary institutions and partisan norms are complex, and new members of parliament are unlikely to possess an innate awareness of optimal behavior. This paper examines how new legislators adopt the behavioral patterns of incumbent members in the 6th European Parliament. The 6th EP provides...

For many years psychological studies of the learning process have used a simulated medical diagnosis task in which symptom configurations are probabilistically related to diseases. Participants are given a set of symptoms and asked to indicate which disease is present, and feedback is given on...

We present an experiment for the study of learning in a complex task which requires both memorisation and the ability to process several pieces of information. The outcome of an action, for which immediate feedback is given, depends on the context (i.e. one of thirty-two sequences of three...

The article presents certain ways of understanding a learning organization and its characteristic features. It also contains the results of a study of twenty–seven Polish enterprises facilitating diagnosis of their learning ability. It has been shown that learning ability is connected with the...

We analyze households' responses to an unanticipated change in consumption opportunities and evaluate their implications for the nature and formation of preferences. We study the tariff experiment conducted by South Central Bell where local telephone tariffs were introduced for the first time in...

We analyze a dynamic principal-agent problem with moral hazard and private learning. Each period the agent faces a choice between two actions: a safe action with known returns (exploitation) and a costly risky action with unknown returns (experimentation). We explicitly characterize the cheapest...

We have developed a method for directly learning relative preferences from histories of comparison information without an intermediate utility computation. Our method infers preferences that are rational in a psychological sense, where agent choices result from Bayesian inference of what to do...

Traditional macroeconomic learning algorithms are misspecified when all agents are learning simultaneously. In this paper, we produce a number of learning algorithms that do not share this failing, and show that this enables them to learn almost any solution, for any parameters, implying...

We make use of an agent-based simulator of organizations with distributed decision-making in order to highlight factors that generate organizational learning curves. We focus on learning curves that arise with decision-makers that make one single, simple decision: routing things to do to those...