Fora, networks and public examinations: the role and significance of public participation in the new regional plan for South East England

This paper overviews the main conceptual frameworks for understanding participatory approaches to land use planning and explores their utility in analysing the experience of a recent regional planning exercise in South East England. In particular it examines the contribution of recent ‘New Institutionalist’ ideas to our understanding of participatory processes and the implications for practice of using them to build strategies of public involvement in policy-making and implementation

Learning the Preferences of Ignorant, Inconsistent Agents

An important use of machine learning is to learn what people value. What posts or photos should a user be shown? Which jobs or activities would a person find rewarding? In each case, observations of people's past choices can inform our inferences about their likes and preferences. If we assume that choices are approximately optimal according to some utility function, we can treat preference inference as Bayesian inverse planning. That is, given a prior on utility functions and some observed choices, we invert an optimal decision-making process to infer a posterior distribution on utility functions. However, people often deviate from approximate optimality. They have false beliefs, their planning is sub-optimal, and their choices may be temporally inconsistent due to hyperbolic discounting and other biases. We demonstrate how to incorporate these deviations into algorithms for preference inference by constructing generative models of planning for agents who are subject to false beliefs and time inconsistency. We explore the inferences these models make about preferences, beliefs, and biases. We present a behavioral experiment in which human subjects perform preference inference given the same observations of choices as our model. Results show that human subjects (like our model) explain choices in terms of systematic deviations from optimal behavior and suggest that they take such deviations into account when inferring preferences.Comment: AAAI 201

Relationship between specific (dis)utility and the frequency of driving a car

An interesting issue in contemporary travel behavior research is whether the transportation demand has to be considered purely derived from underlying activity patterns or whether a utility is also associated with traveling per se. In the latter case, substantial amendments of current planning models would be needed to represent this phenomenon adequately. Earlier research consistently gave evidence of the existence of this specific utility, but its quantification is hindered by a specific measurement problem because survey respondents tend to mingle the utility of traveling and the utility of reaching a destination. The present work defines a methodology to quantify the decrement in the specific utility of driving a car due to the presence of difficulties and self-limiting behaviors. This is in turn responsible for an alteration of driving frequency. A structural equation modeling technique is used for the analysis. The structural submodel represents the complex relationships between socio-economic variables, specific utility, and driving frequency. The measurement submodel defines the specific utility on the basis of reported self-evaluations concerning physical fitness and self-limiting behaviors while driving. An application of the method based on data collected in the 2002 National Transportation Availability and Use Survey is presented. The results show that the decrement of specific utility (which can be seen as a disutility) of driving a car has an important impact on the frequency of performing this activity compared with the derived utility that is customarily modeled through socioeconomic variables

An analysis of commitment strategies in planning: The details

We compare the utility of different commitment strategies in planning. Under a 'least commitment strategy', plans are represented as partial orders and operators are ordered only when interactions are detected. We investigate claims of the inherent advantages of planning with partial orders, as compared to planning with total orders. By focusing our analysis on the issue of operator ordering commitment, we are able to carry out a rigorous comparative analysis of two planners. We show that partial-order planning can be more efficient than total-order planning, but we also show that this is not necessarily so