The Experts below are selected from a list of 303 Experts worldwide ranked by ideXlab platform
David J Smith - One of the best experts on this subject based on the ideXlab platform.
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optimal limited Contingency Planning
arXiv: Artificial Intelligence, 2012Co-Authors: Nicolas Meuleau, David J SmithAbstract:For a given problem, the optimal Markov policy can be considerred as a conditional or contingent plan containing a (potentially large) number of branches. Unfortunately, there are applications where it is desirable to strictly limit the number of decision points and branches in a plan. For example, it may be that plans must later undergo more detailed simulation to verify correctness and safety, or that they must be simple enough to be understood and analyzed by humans. As a result, it may be necessary to limit consideration to plans with only a small number of branches. This raises the question of how one goes about finding optimal plans containing only a limited number of branches. In this paper, we present an any-time algorithm for optimal k-Contingency Planning (OKP). It is the first optimal algorithm for limited Contingency Planning that is not an explicit enumeration of possible contingent plans. By modelling the problem as a Partially Observable Markov Decision Process, it implements the Bellman optimality principle and prunes the solution space. We present experimental results of applying this algorithm to some simple test cases.
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optimal limited Contingency Planning
Uncertainty in Artificial Intelligence, 2002Co-Authors: Nicolas Meuleau, David J SmithAbstract:For a given problem, the optimal Markov policy over a finite horizon is a conditional plan containing a potentially large number of branches. However, there are applications where it is desirable to strictly limit the number of decision points and branches in a plan. This raises the question of how one goes about finding optimal plans containing only a limited number of branches. In this paper, we present an any-time algorithm for optimal k-Contingency Planning. It is the first optimal algorithm for limited Contingency Planning that is not an explicit enumeration of possible contingent plans. By modelling the problem as a partially observable Markov decision process, it implements the Bellman optimality principle and prunes the solution space. We present experimental results of applying this algorithm to some simple test cases.
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UAI - Optimal limited Contingency Planning
2002Co-Authors: Nicolas Meuleau, David J SmithAbstract:For a given problem, the optimal Markov policy over a finite horizon is a conditional plan containing a potentially large number of branches. However, there are applications where it is desirable to strictly limit the number of decision points and branches in a plan. This raises the question of how one goes about finding optimal plans containing only a limited number of branches. In this paper, we present an any-time algorithm for optimal k-Contingency Planning. It is the first optimal algorithm for limited Contingency Planning that is not an explicit enumeration of possible contingent plans. By modelling the problem as a partially observable Markov decision process, it implements the Bellman optimality principle and prunes the solution space. We present experimental results of applying this algorithm to some simple test cases.
Nicolas Meuleau - One of the best experts on this subject based on the ideXlab platform.
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optimal limited Contingency Planning
arXiv: Artificial Intelligence, 2012Co-Authors: Nicolas Meuleau, David J SmithAbstract:For a given problem, the optimal Markov policy can be considerred as a conditional or contingent plan containing a (potentially large) number of branches. Unfortunately, there are applications where it is desirable to strictly limit the number of decision points and branches in a plan. For example, it may be that plans must later undergo more detailed simulation to verify correctness and safety, or that they must be simple enough to be understood and analyzed by humans. As a result, it may be necessary to limit consideration to plans with only a small number of branches. This raises the question of how one goes about finding optimal plans containing only a limited number of branches. In this paper, we present an any-time algorithm for optimal k-Contingency Planning (OKP). It is the first optimal algorithm for limited Contingency Planning that is not an explicit enumeration of possible contingent plans. By modelling the problem as a Partially Observable Markov Decision Process, it implements the Bellman optimality principle and prunes the solution space. We present experimental results of applying this algorithm to some simple test cases.
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incremental Contingency Planning
2003Co-Authors: Richard Dearden, David E. Smith, Nicolas Meuleau, Sailesh Ramakrishnan, Rich WashingtonAbstract:There has been considerable work in AI on Planning under uncertainty. However, this work generally assumes an extremely simple model of action that does not consider continuous time and resources. These assumptions are not reasonable for a Mars rover, which must cope with uncertainty about the duration of tasks, the energy required, the data storage necessary, and its current position and orientation. In this paper, we outline an approach to generating Contingency plans when the sources of uncertainty involve continuous quantities such as time and resources. The approach involves first constructing a "seed" plan, and then incrementally adding contingent branches to this plan in order to improve utility. The challenge is to figure out the best places to insert Contingency branches. This requires an estimate of how much utility could be gained by building a contingent branch at any given place in the seed plan. Computing this utility exactly is intractable, but we outline an approximation method that back propagates utility distributions through a graph structure similar to that of a plan graph.
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optimal limited Contingency Planning
Uncertainty in Artificial Intelligence, 2002Co-Authors: Nicolas Meuleau, David J SmithAbstract:For a given problem, the optimal Markov policy over a finite horizon is a conditional plan containing a potentially large number of branches. However, there are applications where it is desirable to strictly limit the number of decision points and branches in a plan. This raises the question of how one goes about finding optimal plans containing only a limited number of branches. In this paper, we present an any-time algorithm for optimal k-Contingency Planning. It is the first optimal algorithm for limited Contingency Planning that is not an explicit enumeration of possible contingent plans. By modelling the problem as a partially observable Markov decision process, it implements the Bellman optimality principle and prunes the solution space. We present experimental results of applying this algorithm to some simple test cases.
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UAI - Optimal limited Contingency Planning
2002Co-Authors: Nicolas Meuleau, David J SmithAbstract:For a given problem, the optimal Markov policy over a finite horizon is a conditional plan containing a potentially large number of branches. However, there are applications where it is desirable to strictly limit the number of decision points and branches in a plan. This raises the question of how one goes about finding optimal plans containing only a limited number of branches. In this paper, we present an any-time algorithm for optimal k-Contingency Planning. It is the first optimal algorithm for limited Contingency Planning that is not an explicit enumeration of possible contingent plans. By modelling the problem as a partially observable Markov decision process, it implements the Bellman optimality principle and prunes the solution space. We present experimental results of applying this algorithm to some simple test cases.
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Contingency Planning for planetary rovers
2002Co-Authors: Richard Dearden, David E. Smith, Nicolas Meuleau, Sailesh Ramakrishnan, Rich Washington, Daniel ClancyAbstract:There has been considerable work in AI on Planning under uncertainty. But this work generally assumes an extremely simple model of action that does not consider continuous time and resources. These assumptions are not reasonable for a Mars rover, which must cope with uncertainty about the duration of tasks, the power required, the data storage necessary, along with its position and orientation. In this paper, we outline an approach to generating Contingency plans when the sources of uncertainty involve continuous quantities such as time and resources. The approach involves first constructing a "seed" plan, and then incrementally adding contingent branches to this plan in order to improve utility. The challenge is to figure out the best places to insert Contingency branches. This requires an estimate of how much utility could be gained by building a contingent branch at any given place in the seed plan. Computing this utility exactly is intractable, but we outline an approximation method that back propagates utility distributions through a graph structure similar to that of a plan graph.
Saravana Kumar - One of the best experts on this subject based on the ideXlab platform.
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getting help quickly older people and community worker perspectives of Contingency Planning for falls management
Disability and Rehabilitation, 2018Co-Authors: Kimberly Charlton, Carolyn M Murray, Saravana KumarAbstract:AbstractPurpose: Older people living in the community need to plan for getting help quickly if they have a fall. In this paper Planning for falls is referred to as Contingency Planning and is not a falls prevention strategy but rather a falls management strategy. This research explored the perspectives of older people and community workers (CWs) about Contingency Planning for a fall.Method: Using a qualitative descriptive approach, participants were recruited through a community agency that supports older people. In-depth interviews were conducted with seven older people (67–89 years of age) and a focus group was held with seven workers of mixed disciplines from the same agency. Older people who hadn’t fallen were included but were assumed to be at risk of falls because they were in receipt of services. Thematic analysis and concept mapping combined the data from the two participant groups.Results: Four themes including preconceptions about Planning ahead for falling, a fall changes perception, giving, an...
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perspectives of older people about Contingency Planning for falls in the community a qualitative meta synthesis
PLOS ONE, 2017Co-Authors: Kimberly Charlton, Carolyn M Murray, Saravana KumarAbstract:Objective Despite consistent evidence for the positive impact of Contingency Planning for falls in older people, implementation of plans often fail. This is likely due to lack of recognition and knowledge about perspectives of older people about Contingency Planning. The objective of this research was to explore the perspectives of older people living in the community about use of Contingency Planning for getting help quickly after a fall. Method A systematic literature search seeking qualitative research was conducted in April 2014, with no limit placed on date of publication. Medline, EMBASE, Ageline, CINAHL, HealthSource- Nursing/Academic Edition, AMED and Psych INFO databases were searched. Three main concepts were explored and linked using Boolean operators; older people, falls and Contingency Planning. The search was updated until February 2016 with no new articles found. After removal of duplicates, 562 articles were assessed against inclusion and exclusion criteria resulting in six studies for the meta-synthesis. These studies were critically appraised using the McMaster critical appraisal tool. Bespoke data extraction sheets were developed and a meta-synthesis approach was adopted to extract and synthesise findings. Findings Three themes of ‘a mix of attitudes’, ‘careful deliberations’ and ‘a source of anxiety’ were established. Perspectives of older people were on a continuum between regarding Contingency plans as necessary and not necessary. Levels of engagement with the Contingency Planning process seemed associated with acceptance of their risk of falling and their familiarity with available Contingency Planning strategies. Conclusion Avoiding a long lie on the floor following a fall is imperative for older people in the community but there is a lack of knowledge about Contingency Planning for falls. This meta-synthesis provides new insights into this area of health service delivery and highlights that implementation of plans needs to be directed by the older people rather than the health professionals.
Kimberly Charlton - One of the best experts on this subject based on the ideXlab platform.
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getting help quickly older people and community worker perspectives of Contingency Planning for falls management
Disability and Rehabilitation, 2018Co-Authors: Kimberly Charlton, Carolyn M Murray, Saravana KumarAbstract:AbstractPurpose: Older people living in the community need to plan for getting help quickly if they have a fall. In this paper Planning for falls is referred to as Contingency Planning and is not a falls prevention strategy but rather a falls management strategy. This research explored the perspectives of older people and community workers (CWs) about Contingency Planning for a fall.Method: Using a qualitative descriptive approach, participants were recruited through a community agency that supports older people. In-depth interviews were conducted with seven older people (67–89 years of age) and a focus group was held with seven workers of mixed disciplines from the same agency. Older people who hadn’t fallen were included but were assumed to be at risk of falls because they were in receipt of services. Thematic analysis and concept mapping combined the data from the two participant groups.Results: Four themes including preconceptions about Planning ahead for falling, a fall changes perception, giving, an...
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perspectives of older people about Contingency Planning for falls in the community a qualitative meta synthesis
PLOS ONE, 2017Co-Authors: Kimberly Charlton, Carolyn M Murray, Saravana KumarAbstract:Objective Despite consistent evidence for the positive impact of Contingency Planning for falls in older people, implementation of plans often fail. This is likely due to lack of recognition and knowledge about perspectives of older people about Contingency Planning. The objective of this research was to explore the perspectives of older people living in the community about use of Contingency Planning for getting help quickly after a fall. Method A systematic literature search seeking qualitative research was conducted in April 2014, with no limit placed on date of publication. Medline, EMBASE, Ageline, CINAHL, HealthSource- Nursing/Academic Edition, AMED and Psych INFO databases were searched. Three main concepts were explored and linked using Boolean operators; older people, falls and Contingency Planning. The search was updated until February 2016 with no new articles found. After removal of duplicates, 562 articles were assessed against inclusion and exclusion criteria resulting in six studies for the meta-synthesis. These studies were critically appraised using the McMaster critical appraisal tool. Bespoke data extraction sheets were developed and a meta-synthesis approach was adopted to extract and synthesise findings. Findings Three themes of ‘a mix of attitudes’, ‘careful deliberations’ and ‘a source of anxiety’ were established. Perspectives of older people were on a continuum between regarding Contingency plans as necessary and not necessary. Levels of engagement with the Contingency Planning process seemed associated with acceptance of their risk of falling and their familiarity with available Contingency Planning strategies. Conclusion Avoiding a long lie on the floor following a fall is imperative for older people in the community but there is a lack of knowledge about Contingency Planning for falls. This meta-synthesis provides new insights into this area of health service delivery and highlights that implementation of plans needs to be directed by the older people rather than the health professionals.
Allan Mcconnell - One of the best experts on this subject based on the ideXlab platform.
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Contingency Planning for crisis management recipe for success or political fantasy
Policy and Society, 2011Co-Authors: Kerstin Eriksson, Allan McconnellAbstract:Contingency Planning is widely considered to be an essential role of public authorities. Anticipation of what may happen, coupled with the prior allocation of resources, personnel, equipment, crisis control rooms, tasks, responsibilities and decision guidance/rules, is assumed to maximise the chances of a successful response in the event of a crisis. However, this paper proposes that the relationship between crisis Planning and crisis management outcomes is more complex and nuanced relationship the often assumed. Contingency Planning which is successful in the pre-crisis stage, does not guarantee a successful crisis response. Correspondingly, Contingency Planning failures in the pre-crisis stage, do not automatically lead to a flawed crisis response. The reasons rest primarily with the multiple influences on crisis responses – only some of which can be anticipated and planned for. The conclusion provides policy-oriented and analytical reflections which recognise the value of Contingency Planning, while suggesting that we should not inflate our expectation of Contingency planners or rush too quickly to vilify them for a lack of adequate preparations.