Understanding and extending Graphplan

Kambhampati, Subbarao; Parker, Eric P.; Lambrecht, Eric

doi:10.1007/3-540-63912-8_91

Cited by 41 publications

(37 citation statements)

References 4 publications

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“…The Graphplan search is similar to a CSP resolution process (Kambhampati, Lambrecht, & Parker, 1997;Kambhampati, 2000). Consequently, the application of CSP heuristics to a Graphplan approach seems to be a straightforward result.…”

Section: Heuristic Search In Temporal Planningmentioning

confidence: 99%

Organizational commitment and its effects on organizational citizenship behavior in a high-unemployment environment

Devece

Palacios‐Marqués

Alguacil

2016

Journal of Business Research

110

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Many planning domains have to deal with temporal features that can be expressed using durations that are associated to actions. Unfortunately, the conservative model of actions used in many existing temporal planners is not adequate for domains which require more expressive models. This paper presents a temporal planning approach that combines the principles of Graphplan and TGP and uses the information calculated in the planning graph to deal with a non-conservative model of actions that include local conditions and effects. In this approach, we propose two strategies for search. The first one is based on the Graphplan backward search. The second one is based on a least-commitment and heuristic search, and it attempts to overcome the main limitations of a chronological backtracking search when dealing with large temporal problems. This search has proved to be beneficial in the scalability of the planner and the experiments show that a planner using this new search is competitive with other state-of-the-art planners w.r.t. the plan quality 1 .

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Section: Heuristic Search In Temporal Planningmentioning

confidence: 99%

Organizational commitment and its effects on organizational citizenship behavior in a high-unemployment environment

Devece

Palacios‐Marqués

Alguacil

2016

Journal of Business Research

110

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“…In the following years, new algorithms have been developed by AI planning theoreticians looking for ways of producing more efficient planners. The GraphPlan algorithm (Blum and Fust, 1997) is the best known of these Kambhampati et al (1997), Weld et al (1998), Cayrol et al (2000 to name only a few. If one were to start in the year 2000, would this approach be better as a way of generating plant operating procedures than the ones discussed above?…”

Section: Results and Conclusionmentioning

confidence: 99%

Planning plant operating procedures for chemical plant

Aylett

Soutter²,

Petley

et al. 2001

Engineering Applications of Artificial Intelligence

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All industrial plants require an extensive set of operating procedures. This paper discusses the use of hierarchical nonlinear leastcommitment AI planning technology to generate plant operating procedures for chemical process plant. It considers the handling of flow through the interfacing of a valve sequencing subplanner, the handling of safety through the mechanism of goals of prevention, and the use of pairs as a way of mutually constraining planning variables and increasing planning efficiency. It concludes with some results and discussion of the advantages of the approach. #

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“…To cope with this problem, we have used a similar approach to (Kambhampati et al, 1997). We use means-ends analysis in the Graphplan algorithm, by first producing an operators-graph (Smith and Peot, 1996) using a backward-chaining process starting from the goal state.…”

Section: Distributed Graphplan With Operators-graphmentioning

confidence: 99%

COORDINATION IN OPEN AND UNSTRUCTURED INTELLIGENT AGENT SOCIETIES - Using Distributed Planners on Top of a Semantic Overlay Network

Lopes

Botelho

2010

Proceedings of the 2nd International Conference on Agents and Artificial Intelligence

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Abstract:Collaborative environments, where multiple heterogeneous agents (managing several resources) can cooperate in pursuing common and individual goals, are a step forward in creating real-world agent societies. However, current research in agent negotiation and in service coordination is still not enough for building such an agent-based society, capable of jointly solving complex planning problems and still achieve overall good performance. Most often, current work relies on either some centralised component or pre-defined social structure, which can compromise the system in terms of scalability, openness and robustness, and fails to address general problems. By using efficient network search algorithms and network evolution techniques it is possible to build and maintain a semantic overlay network from a totally unstructured distributed network, which in turn will simplify and optimize the distributed planning process amongst heterogeneous agents. We developed distributed versions of well-known planners that operate on top of the referred semantic overlay network and through a set of tests (using different scenarios) we were able to determine which is the best algorithm.

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Understanding and extending Graphplan

Cited by 41 publications

References 4 publications

Organizational commitment and its effects on organizational citizenship behavior in a high-unemployment environment

Organizational commitment and its effects on organizational citizenship behavior in a high-unemployment environment

Planning plant operating procedures for chemical plant

COORDINATION IN OPEN AND UNSTRUCTURED INTELLIGENT AGENT SOCIETIES - Using Distributed Planners on Top of a Semantic Overlay Network

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