Tradeoffs in the utility of learned knowledge

Planning systems which make use of domain theories can produce more accurate plans and achieve more goals as the quality of their domain knowledge improves. MTR, a multi-strategy learning system, was designed to learn from system failures and improve domain knowledge used in planning. However, augmented domain knowledge can decrease planning efficiency. We describe how improved knowledge that becomes expensive to use can be approximated to yield calculated tradeoffs in accuracy and efficiency

Storing and Indexing Plan Derivations through Explanation-based Analysis of Retrieval Failures

Case-Based Planning (CBP) provides a way of scaling up domain-independent planning to solve large problems in complex domains. It replaces the detailed and lengthy search for a solution with the retrieval and adaptation of previous planning experiences. In general, CBP has been demonstrated to improve performance over generative (from-scratch) planning. However, the performance improvements it provides are dependent on adequate judgements as to problem similarity. In particular, although CBP may substantially reduce planning effort overall, it is subject to a mis-retrieval problem. The success of CBP depends on these retrieval errors being relatively rare. This paper describes the design and implementation of a replay framework for the case-based planner DERSNLP+EBL. DERSNLP+EBL extends current CBP methodology by incorporating explanation-based learning techniques that allow it to explain and learn from the retrieval failures it encounters. These techniques are used to refine judgements about case similarity in response to feedback when a wrong decision has been made. The same failure analysis is used in building the case library, through the addition of repairing cases. Large problems are split and stored as single goal subproblems. Multi-goal problems are stored only when these smaller cases fail to be merged into a full solution. An empirical evaluation of this approach demonstrates the advantage of learning from experienced retrieval failure.Comment: See http://www.jair.org/ for any accompanying file

The blind leading the blind: Mutual refinement of approximate theories

The mutual refinement theory, a method for refining world models in a reactive system, is described. The method detects failures, explains their causes, and repairs the approximate models which cause the failures. The approach focuses on using one approximate model to refine another

Increasingly automated procedure acquisition in dynamic systems

Procedures are widely used by operators for controlling complex dynamic systems. Currently, most development of such procedures is done manually, consuming a large amount of paper, time, and manpower in the process. While automated knowledge acquisition is an active field of research, not much attention has been paid to the problem of computer-assisted acquisition and refinement of complex procedures for dynamic systems. The Procedure Acquisition for Reactive Control Assistant (PARC), which is designed to assist users in more systematically and automatically encoding and refining complex procedures. PARC is able to elicit knowledge interactively from the user during operation of the dynamic system. We categorize procedure refinement into two stages: diagnosis - diagnose the failure and choose a repair - and repair - plan and perform the repair. The basic approach taken in PARC is to assist the user in all steps of this process by providing increased levels of assistance with layered tools. We illustrate the operation of PARC in refining procedures for the control of a robot arm

Issues in front-end decision-making on projects

The importance of the front-end decision-making phase in projects is being increasingly recognized - the need to do the right project is on a par with doing the project right. This area is underrepresented in the literature, but there are a number of key themes that run throughout, identifying key issues or difficulties during this stage. This article looks at some of these themes and includes: the need for alignment between organizational strategy and the project concept; dealing with complexity, in particular the systemicity and interrelatedness within project decisions; consideration of the ambiguity implicit in all major projects; taking into account psychological and political biases within estimation of benefits and costs; consideration of the social geography and politics within decision-making groups; and preparation for the turbulence within the project environment, including the maintenance of strategic alignment

Failure and Strategic Projects: Australias Asia-Pacific Vision

This paper uses Australia’s 1980s shift to a new accumulation strategy of ‘international competitiveness’ to examine the role of failure in shaping state strategic projects. The paper argues that the Australian strategy’s gradual shift from an interventionist to a market-led orientation played out in competing representations of failure. Whether particular policies were perceived as failures depended not only on their material effects, but also on the ways in which failure was defined and on the values underpinning those definitions. As representations of failure establish the boundaries between the incremental adaptations that stabilise an accumulation strategy and the more radical failures characteristic of crisis, they illuminate how processes of discursive selectivity ‘fix’ state projects’ temporal, scalar and spatial dimension

Applying HRO and resilience engineering to construction: Barriers and opportunities

High reliability organising (HRO) and resilience engineering (RE) have emerged as key concepts in safety management which promise a move away from bureaucracy and a means to manage safety without sacrificing performance. However, attempts to apply these ideas outside the ultra-safe sectors within which they developed have so far been limited. This paper uses the construction industry as a test case to explore the applicability of HRO and RE in a less highly regulated context. Through this discussion the research gaps are highlighted which have prevented the expansion of these new approaches into new sectors. The project-based nature, transient workforce, widespread outsourcing of labour and financial pressure of the construction sector limit opportunities for investment in employees and learning from experience; hence, developing principles advocated by HRO and RE such as management commitment, sensitivity to the frontline, prioritisation of safety, empowerment of employees, and a just culture presents a significant challenge. In spite of these barriers, there are also opportunities to be considered for construction to incorporate aspects of HRO and RE at an employee-centred level rather than organisational: Aspects of mindfulness and imagination; RE’s progressive understanding of accidents; and its holistic approach to cultivating resilience. It is argued that these opportunities offer a useful perspective for reframing safety debates in construction. The paper concludes with a research agenda which puts forward the need to extend and adapt aspects of HRO and RE in order to tackle some of the key characteristics of construction, namely subcontractor networks and temporary projects

A Domain-Independent Algorithm for Plan Adaptation

The paradigms of transformational planning, case-based planning, and plan debugging all involve a process known as plan adaptation - modifying or repairing an old plan so it solves a new problem. In this paper we provide a domain-independent algorithm for plan adaptation, demonstrate that it is sound, complete, and systematic, and compare it to other adaptation algorithms in the literature. Our approach is based on a view of planning as searching a graph of partial plans. Generative planning starts at the graph's root and moves from node to node using plan-refinement operators. In planning by adaptation, a library plan - an arbitrary node in the plan graph - is the starting point for the search, and the plan-adaptation algorithm can apply both the same refinement operators available to a generative planner and can also retract constraints and steps from the plan. Our algorithm's completeness ensures that the adaptation algorithm will eventually search the entire graph and its systematicity ensures that it will do so without redundantly searching any parts of the graph.Comment: See http://www.jair.org/ for any accompanying file

Hayek and Economic Policy (The Austrian Road to the Third Way).

By examining Hayek’s approach to economic policy, this paper tries to show that his understanding of a free-market society was ambiguous, if not contradictory. Hayek was indeed following the Austrian tradition by rejecting technocratic views of policy-making. Nevertheless, he advocated a constitutional approach ultimately based on the rule of law created behind a veil of ignorance. Regulation and a fairly extensive welfare state are not ruled out either, and are subject to evaluation through a mix of rule of law (what that means), public opinion, common sense. After close inspection of the Road to Serfdom, the Constitution of Liberty, Law, Legislation and Liberty this contribution concludes that not only does Hayek fail to provide clear answers to the fundamental questions of economic policy. He also advocates a Third Way characterised by enlightened social engineering. In particular, the state has the duty to provide a suitable framework for the individual to develop his action, and to meet those social needs that the market fails to satisfy.