Rational Deployment of CSP Heuristics

Heuristics are crucial tools in decreasing search effort in varied fields of AI. In order to be effective, a heuristic must be efficient to compute, as well as provide useful information to the search algorithm. However, some well-known heuristics which do well in reducing backtracking are so heavy that the gain of deploying them in a search algorithm might be outweighed by their overhead. We propose a rational metareasoning approach to decide when to deploy heuristics, using CSP backtracking search as a case study. In particular, a value of information approach is taken to adaptive deployment of solution-count estimation heuristics for value ordering. Empirical results show that indeed the proposed mechanism successfully balances the tradeoff between decreasing backtracking and heuristic computational overhead, resulting in a significant overall search time reduction.Comment: 7 pages, 2 figures, to appear in IJCAI-2011, http://www.ijcai.org

Assessing Renewable Energy Policy Transfer from Germany to Morocco

Given the tremendous energy challenges Morocco faces, and its potential role as an exporter of green electricity to Europe, the country has been particularly targeted by Germany’s efforts to promote the uptake of renewable energies abroad. This paper explores whether ideas and policies in the field of renewable energy effectively traveled through transfer channels established between Germany and Morocco. In particular, the question of how Morocco’s policy objectives shaped the result of transfer processes is discussed, shedding light on a currently under-researched determinant for policy transfer. Drawing upon forty-five semi-structured interviews with Moroccan, German, and international stakeholders, as well as card-ranking exercises, the article provides first-hand insights into the dynamics and drivers of Morocco’s “energy transition”. Findings presented in the article show that differing policy objectives did not preclude the transfer of ideas between Germany and Morocco, but shaped its outcome with regard to policy instrument selection. While basic policy orientations in favour of renewable energies were facilitated by transferred knowledge, a perceived incompatibility between domestic policy objectives and the policy instruments used in the foreign model led to selective lesson-drawing from the German example. This finding underlines the importance for “senders” who wish to actively promote sustainable energy policies abroad to adapt outreach strategies to the policy objectives of potential followers

Reducing CO2 emissions from residential energy use

To achieve European Union (EU) greenhouse gas emissions of 80–95% below 1990 levels by 2050, CO2 emissions from residential energy consumption must be substantially reduced. Recognition of this has led to the introduction of a range of policy instruments at both EU and member state level. These policies are examined for the EU and the UK, first by grouping them into three ‘pillars of policy’ – standards and engagement, markets and pricing, and strategic investment (each of which focus on different ‘domains of change’ embodying different economic processes) – and then by assessing the strengths and weaknesses of each pillar in terms of instrument coverage and effectiveness. Strengths and weaknesses common to both UK and EU policy landscapes are found, including a comprehensive but broadly ineffective standards and engagement pillar of policy, and an ineffective markets and pricing landscape (including effective subsidization of energy consumption in the UK, permitted by the EU), with poor coverage. The strategic investment landscape is found (until recently) to be substantially stronger in the UK compared with EU instruments and requirements. Priority reform actions are also proposed to address the weaknesses identified. The paper also offers discussion of recent policy developments in the UK

Empirical evaluation of Soft Arc Consistency algorithms for solving Constraint Optimization Problems

A large number of problems in Artificial Intelligence and other areas of science can be viewed as special cases of constraint satisfaction or optimization problems. Various approaches have been widely studied, including search, propagation, and heuristics. There are still challenging real-world COPs that cannot be solved using current methods. We implemented and compared several consistency propagation algorithms, which include W-AC*2001, EDAC, VAC, and xAC. Consistency propagation is a classical method to reduce the search space in CSPs, and has been adapted to COPs. We compared several consistency propagation algorithms, based on the resemblance between the optimal value ordering and the approximate value ordering generated by them. The results showed that xAC generated value orderings of higher quality than W-AC*2001 and EDAC. We evaluated some novel hybrid methods for solving COPs. Hybrid methods combine consistency propagation and search in order to reach a good solution as soon as possible and prune the search space as much as possible. We showed that the hybrid method which combines the variant TP+OnOff and branch-and-bound search performed fewer constraint checks and searched fewer nodes than others in solving random and real-world COPs

Working Notes from the 1992 AAAI Spring Symposium on Practical Approaches to Scheduling and Planning

The symposium presented issues involved in the development of scheduling systems that can deal with resource and time limitations. To qualify, a system must be implemented and tested to some degree on non-trivial problems (ideally, on real-world problems). However, a system need not be fully deployed to qualify. Systems that schedule actions in terms of metric time constraints typically represent and reason about an external numeric clock or calendar and can be contrasted with those systems that represent time purely symbolically. The following topics are discussed: integrating planning and scheduling; integrating symbolic goals and numerical utilities; managing uncertainty; incremental rescheduling; managing limited computation time; anytime scheduling and planning algorithms, systems; dependency analysis and schedule reuse; management of schedule and plan execution; and incorporation of discrete event techniques