International Conference on Automated Planning and Scheduling最新文献

On Using Action Inheritance and Modularity in PDDL Domain Modelling 动作继承和模块化在PDDL领域建模中的应用

International Conference on Automated Planning and Scheduling Pub Date : 2023-07-01 DOI: 10.1609/icaps.v33i1.27203

A. Lindsay

{"title":"On Using Action Inheritance and Modularity in PDDL Domain Modelling","authors":"A. Lindsay","doi":"10.1609/icaps.v33i1.27203","DOIUrl":"https://doi.org/10.1609/icaps.v33i1.27203","url":null,"abstract":"The PDDL modelling problem is known to be challenging, time consuming and error prone. This has led researchers to investigate methods of supporting the modelling process. One particular avenue is to adapt tools and techniques that have proven useful in software engineering to support the modelling process. We observe that concepts, such as inheritance and modularity have not been fully explored in the context of modelling PDDL planning models. Within software engineering these concepts help to organise and provide structure to code, which can make it easier to read, debug, and reuse code. In this work we consider inheritance and modularity and their use in PDDL action descriptions, and how these can have a similar impact on the PDDL modelling process. We\u0000define an extension to PDDL and develop appropriate tools to compile models using these extensions, both directly from the command line and through the Visual Studio Code PDDL extension. We report on our use of inheritance and modularity when modelling a planning model for a companion robot scenario. We also discuss the benefits of exploiting the inheritance hierarchy in other modules within our robot system.","PeriodicalId":239898,"journal":{"name":"International Conference on Automated Planning and Scheduling","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122713180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Generalizing Action Justification and Causal Links to Policies 概括行动的理由和政策的因果关系

International Conference on Automated Planning and Scheduling Pub Date : 2023-07-01 DOI: 10.1609/icaps.v33i1.27221

S. Sreedharan, Christian Muise, Subbarao Kambhampati

引用次数: 0

A Column Generation Approach to Correlated Simple Temporal Networks 关联简单时态网络的列生成方法

International Conference on Automated Planning and Scheduling Pub Date : 2023-07-01 DOI: 10.1609/icaps.v33i1.27207

Andrew Murray, A. Arulselvan, Michael Cashmore, M. Roper, J. Frank

{"title":"A Column Generation Approach to Correlated Simple Temporal Networks","authors":"Andrew Murray, A. Arulselvan, Michael Cashmore, M. Roper, J. Frank","doi":"10.1609/icaps.v33i1.27207","DOIUrl":"https://doi.org/10.1609/icaps.v33i1.27207","url":null,"abstract":"Probabilistic Simple Temporal Networks (PSTN) represent scheduling problems under temporal uncertainty. Strong controllability (SC) of PSTNs involves finding a schedule to a PSTN that maximises the probability that all constraints are satisfied (robustness). Previous approaches to this problem assume independence of probabilistic durations, and approximate the risk by bounding it above using Boole’s inequality. This gives no guarantee of finding the schedule optimising robustness, and fails to consider correlations between probabilistic durations that frequently arise in practical applications. In this paper, we formally define the Correlated Simple Temporal Network (Corr-STN) which generalises the PSTN by removing the restriction of independence. We show that the problem of Corr-STN SC is convex for a large class of multivariate (log-concave) distributions. We then introduce an algorithm capable of finding optimal SC schedules to Corr-STNs, using the column generation method. Finally, we validate our approach on a number of Corr-STNs and find that our method offers more robust solutions when compared with prior approaches.","PeriodicalId":239898,"journal":{"name":"International Conference on Automated Planning and Scheduling","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130002084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robust Metric Hybrid Planning in Stochastic Nonlinear Domains Using Mathematical Optimization 基于数学优化的随机非线性域鲁棒度量混合规划

International Conference on Automated Planning and Scheduling Pub Date : 2023-07-01 DOI: 10.1609/icaps.v33i1.27216

B. Say

引用次数: 0

Convexity Hierarchies in Grid Networks 网格网络中的凸性层次结构

International Conference on Automated Planning and Scheduling Pub Date : 2023-07-01 DOI: 10.1609/icaps.v33i1.27178

Johannes Blum, Ruoying Li, Sabine Storandt

{"title":"Convexity Hierarchies in Grid Networks","authors":"Johannes Blum, Ruoying Li, Sabine Storandt","doi":"10.1609/icaps.v33i1.27178","DOIUrl":"https://doi.org/10.1609/icaps.v33i1.27178","url":null,"abstract":"Several algorithms for path planning in grid networks rely on graph decomposition to reduce the search space size; either by constructing a search data structure on the components, or by using component information for A* guidance.\u0000The focus is usually on obtaining components of roughly equal size with few boundary nodes each. In this paper, we consider the problem of splitting a graph into convex components. A convex component is characterized by the property that for all pairs of its members, the shortest path between them is also contained in it. Thus, given a source node, a target node, and a (small) convex component that contains both of them, path planning can be restricted to this component without compromising optimality. We prove that it is NP-hard to find a balanced node separator that splits a given graph into convex components. However, we also present and evaluate heuristics for (hierarchical) convex decomposition of grid networks that perform well across various benchmarks. Moreover, we describe how existing path planning methods can benefit from the computation of convex components. As one main outcome, we show that contraction hierarchies become up to an order of magnitude faster on large grids when the contraction order is derived from a convex graph decomposition.","PeriodicalId":239898,"journal":{"name":"International Conference on Automated Planning and Scheduling","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124434131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automatic Metamorphic Test Oracles for Action-Policy Testing 用于动作策略测试的自动变形测试预言机

International Conference on Automated Planning and Scheduling Pub Date : 2023-07-01 DOI: 10.1609/icaps.v33i1.27185

Jan Eisenhut, Á. Torralba, M. Christakis, Jörg Hoffmann

{"title":"Automatic Metamorphic Test Oracles for Action-Policy Testing","authors":"Jan Eisenhut, Á. Torralba, M. Christakis, Jörg Hoffmann","doi":"10.1609/icaps.v33i1.27185","DOIUrl":"https://doi.org/10.1609/icaps.v33i1.27185","url":null,"abstract":"Testing is a promising way to gain trust in learned action policies π. \u0000Prior work on action-policy testing in AI planning formalized bugs\u0000as states t where π is sub-optimal with respect to a given testing\u0000objective. Deciding whether or not t is a bug is as hard as (optimal)\u0000planning itself. How can we design test oracles able to recognize some\u0000states t to be bugs efficiently? Recent work introduced metamorphic\u0000oracles which compare policy behavior on state pairs (s,t) where t is\u0000easier to solve; if π performs worse on t than on s, we know that t\u0000is a bug. Here, we show how to automatically design such oracles in\u0000classical planning, based on simulation relations between states. We\u0000introduce two oracle families of this kind: first, morphing query\u0000states t to obtain suitable s; second, maintaining and comparing upper\u0000bounds on h* across the states encountered during testing. Our\u0000experiments on ASNet policies show that these oracles can find bugs\u0000much more quickly than the existing alternatives, which are\u0000search-based; and that the combination of our oracles with\u0000search-based ones almost consistently dominates all other oracles.","PeriodicalId":239898,"journal":{"name":"International Conference on Automated Planning and Scheduling","volume":"214 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116172521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

W-restrained Bidirectional Bounded-Suboptimal Heuristic Search w约束双向有界次优启发式搜索

International Conference on Automated Planning and Scheduling Pub Date : 2023-07-01 DOI: 10.1609/icaps.v33i1.27175

Dor Atzmon, Shahaf S. Shperberg, Netanel Sabah, Ariel Felner, Nathan R Sturtevant

引用次数: 0

Dynamic Weight Setting for Personnel Scheduling with Many Objectives 多目标人员调度的动态权值设置

International Conference on Automated Planning and Scheduling Pub Date : 2023-07-01 DOI: 10.1609/icaps.v33i1.27231

Lucas Kletzander, Nysret Musliu

{"title":"Dynamic Weight Setting for Personnel Scheduling with Many Objectives","authors":"Lucas Kletzander, Nysret Musliu","doi":"10.1609/icaps.v33i1.27231","DOIUrl":"https://doi.org/10.1609/icaps.v33i1.27231","url":null,"abstract":"When large sets of constraints and objectives are combined in a practical optimization problem, managing all these potentially conflicting goals can become very difficult and might require to solve an instance multiple times. First, an instance might be infeasible with the current constraints, in which case our system introduces a novel violation score to help identify the constraints that need to be relaxed for the next run. Second, multiple objectives are often combined using a linear combination with hand-crafted weights, which are very difficult to set such that the result matches the expectations regarding the balance between individual objectives. Instead, the user can tell our system particular thresholds for the expected changes in objectives, e.g., to reduce objective 1 by 10 % while not increasing objective 2 by more than 5 %. Dynamic weight setting automatically adapts the weights to reach these thresholds or uses the violation scores to explain reasons for not reaching thresholds. It can not only be used for soft constraints, but also to determine weights when hard constraints are internally represented as soft constraints in meta-heuristics. While the methodology is general, we have implemented it in the context of a personnel scheduling framework of our industry partner and present a detailed evaluation on the domain of Bus Driver Scheduling, where its benefits can be seen in multiple scenarios.","PeriodicalId":239898,"journal":{"name":"International Conference on Automated Planning and Scheduling","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125890234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Best-First Search Algorithm for FOND Planning and Heuristic Functions to Optimize Decompressed Solution Size 一种最佳优先搜索算法的FOND规划和启发式函数优化解压缩大小

International Conference on Automated Planning and Scheduling Pub Date : 2023-07-01 DOI: 10.1609/icaps.v33i1.27205

Frederico Messa, A. Pereira

{"title":"A Best-First Search Algorithm for FOND Planning and Heuristic Functions to Optimize Decompressed Solution Size","authors":"Frederico Messa, A. Pereira","doi":"10.1609/icaps.v33i1.27205","DOIUrl":"https://doi.org/10.1609/icaps.v33i1.27205","url":null,"abstract":"In this work, we study fully-observable non-deterministic (FOND) planning, which models uncertainty through actions with non-deterministic effects. We present a best-first heuristic search algorithm called AND* that searches the policy-space of the FOND task to find a solution policy. We generalize the concepts of optimality, admissibility, and goal-awareness for FOND. Using these new concepts, we formalize the concept of heuristic functions that can guide a policy-space search. We analyze different aspects of the general structure of FOND solutions to introduce and characterize a set of FOND heuristics that estimate how far a policy is from becoming a solution. One of these heuristics applies a novel insight. Guided by them AND* returns only solutions with the minimal possible number of mapped states. We systematically study these FOND heuristics theoretically and empirically. We observe that our best heuristic makes AND* much more effective than the straightforward heuristics. We believe that our work allows a better understanding of how to design algorithms and heuristics to solve FOND tasks.","PeriodicalId":239898,"journal":{"name":"International Conference on Automated Planning and Scheduling","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124825579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Efficient Reasoning about Infeasible One Machine Sequencing 不可行的单机排序的有效推理

International Conference on Automated Planning and Scheduling Pub Date : 2023-07-01 DOI: 10.1609/icaps.v33i1.27204

R. Mencía, Carlos Mencía, Joao Marques-Silva

引用次数: 0