Significant scholarship has focused on accommodating diverse age groups in urban public environments. However, intergenerational approaches emphasizing engagement between generations represent an emerging area of research and practice. This review synthesizes literature from planning cognate fields the need for benefits space, as well design policy interventions. The results advance understandi...

ions and hierarchical approaches While the envelope extension method ignores portions of the state space, other techniques have considered abstractions of the state space that try to group together sets of states that behave similarly under the chosen actions of the optimal policy. Boutilier and Dearden (Boutilier & Dearden 1994) assume a representation for actions that is similar to that of Bu...

Parcel data on residential land conversion are used to investigate how land use externalities influence the rate of development and modify policies designed to manage urban growth and preserve open space. Several ‘‘smart growth’’ policies are found to significantly influence land conversion, including a development clustering policy that concentrates development and generates preserved open spa...

Users want inference to be both fast and accurate, but quality often comes at the cost of speed. The field has experimented with approximate inference algorithms that make different speed-accuracy tradeoffs (for particular problems and datasets). We aim to explore this space automatically, focusing here on the case of agenda-based syntactic parsing [12]. Unfortunately, off-the-shelf reinforceme...

This article presents the results of a survey carried out at two space outreach events in the UK aimed at characterising "the public for space exploration" and measuring public support for space exploration. Attitude towards space exploration and policy preferences were used as measures of public support. The sample involved 744 respondents and was mainly composed of adults between 25 and 45 ye...

This paper introduces a two-phase approach to solve average cost Markov decision processes, which is based on state space embedding or time aggregation. In the first phase, time aggregation is applied for policy optimization in a prescribed subset of the state space, and a novel result is applied to expand the evaluation to the whole state space. This evaluation is then used in the second phase...