1. Benzeval M, Judge K, Whitehead M. Tackling inequalities in health. An agenda for action. London: King’s Fund; 1995. 2. Ben-Shlomo Y, Marmot M. Policy options for managing health inequalities in industrial and post-industrial countries. En: Strickland SS, Shetty PS, editors. Human biology and social inequality. Cambridge: Cambridge University Press; 1998. p. 308-30. 3. Acheson D, Barker D, Ch...

Policy gradient is an efficient technique for improving a policy in a reinforcement learning setting. However, vanilla online variants are on-policy only and not able to take advantage of off-policy data. In this paper we describe a new technique that combines policy gradient with off-policy Q-learning, drawing experience from a replay buffer. This is motivated by making a connection between th...

the field of cognitive psychology has increasingly provided scientific insights to explore how humans are subject to unconscious sources of evidentiary bias, leading to errors that can affect judgement and decision-making. increasingly these insights are being applied outside the realm of individual decision-making to the collective arena of policy-making as well. a recent editorial in this jou...

In this paper, I attempt to bring together approaches to literacy in theory and in practice, drawing upon various activities I have been involved in over the years–research in Iranian villages during the 1970s; linking research and theory to literacy policy, with particular reference to a contribution to the Unesco Global Monitoring Report in 2004 and involvement in an ongoing adult literacy tr...

I study a model of dynamic policy making in which citizens do not have complete knowledge of how policies are mapped into outcomes. They learn about the mapping through repeated elections as policies are implemented and outcomes observed. I characterize for this environment the policy trajectory with impatient voters. I find that through experimentation good policies are frequently found. Howev...

The problem of online learning and optimization of unknown Markov jump affine models is considered. An online learning policy, referred to as Markovian simultaneous perturbations stochastic approximation (MSPSA), is proposed for two different optimization objectives: (i) the quadratic cost minimization of the regulation problem and (ii) the revenue (profit) maximization problem. It is shown tha...

The paper presents recent insights from the ongoing FORLEARN project, which aims to develop Foresight theory and practise by supporting the sharing of experience (“mutual learning”) in Europe. Six functions of Foresight for policy-making are elaborated on: 1. Informing policy: generating insights regarding the dynamics of change, future challenges and options, along with new ideas, and transmit...