28,682 research outputs found

    Temporal Data Modeling and Reasoning for Information Systems

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    Temporal knowledge representation and reasoning is a major research field in Artificial Intelligence, in Database Systems, and in Web and Semantic Web research. The ability to model and process time and calendar data is essential for many applications like appointment scheduling, planning, Web services, temporal and active database systems, adaptive Web applications, and mobile computing applications. This article aims at three complementary goals. First, to provide with a general background in temporal data modeling and reasoning approaches. Second, to serve as an orientation guide for further specific reading. Third, to point to new application fields and research perspectives on temporal knowledge representation and reasoning in the Web and Semantic Web

    Simple Stochastic Temporal Constraint Networks

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    Many artificial intelligence tasks (e.g., planning, situation assessment, scheduling) require reasoning about events in time. Temporal constraint networks offer an elegant and often computationally efficient framework for such temporal reasoning tasks. Temporal data and knowledge available in some domains is necessarily imprecise - e.g., as a result of measurement errors associated with sensors. This paper introduces stochastic temporal constraint networks thereby extending constraint-based approaches to temporal reasoning with precise temporal knowledge to handle stochastic imprecision. The paper proposes an algorithm for inference of implicit stochastic temporal constraints from a given set of explicit constraints. It also introduces a stochastic version of the temporal constraint network consistency problem and describes techniques for solving it under certain simplifying assumptions

    Reasoning about real-time systems with temporal interval logic constraints on multi-state automata

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    Models of real-time systems using a single paradigm often turn out to be inadequate, whether the paradigm is based on states, rules, event sequences, or logic. A model-based approach to reasoning about real-time systems is presented in which a temporal interval logic called TIL is employed to define constraints on a new type of high level automata. The combination, called hierarchical multi-state (HMS) machines, can be used to model formally a real-time system, a dynamic set of requirements, the environment, heuristic knowledge about planning-related problem solving, and the computational states of the reasoning mechanism. In this framework, mathematical techniques were developed for: (1) proving the correctness of a representation; (2) planning of concurrent tasks to achieve goals; and (3) scheduling of plans to satisfy complex temporal constraints. HMS machines allow reasoning about a real-time system from a model of how truth arises instead of merely depending of what is true in a system

    PDDL2.1: An extension of PDDL for expressing temporal planning domains

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    In recent years research in the planning community has moved increasingly towards application of planners to realistic problems involving both time and many types of resources. For example, interest in planning demonstrated by the space research community has inspired work in observation scheduling, planetary rover ex ploration and spacecraft control domains. Other temporal and resource-intensive domains including logistics planning, plant control and manufacturing have also helped to focus the community on the modelling and reasoning issues that must be confronted to make planning technology meet the challenges of application. The International Planning Competitions have acted as an important motivating force behind the progress that has been made in planning since 1998. The third competition (held in 2002) set the planning community the challenge of handling time and numeric resources. This necessitated the development of a modelling language capable of expressing temporal and numeric properties of planning domains. In this paper we describe the language, PDDL2.1, that was used in the competition. We describe the syntax of the language, its formal semantics and the validation of concurrent plans. We observe that PDDL2.1 has considerable modelling power --- exceeding the capabilities of current planning technology --- and presents a number of important challenges to the research community

    Multiple relaxations in temporal planning

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    CRIKEY is a planner that separates out the scheduling from the classical parts of temporal planning. This can be seen as a relaxation of the temporal information during the classical planning phase. Relaxations in planning are used to guide the search. However, the quality of the relaxation greatly affects the performance of the planner, and in some cases can lead the search into a dead end. This can happen whilst separating out the planning and scheduling problems, leading to the production of an unschedulable plan. CRIKEY can detect these cases and change the relaxation accordingly

    Hierarchical task network approach for time and budget constrained construction project planning

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    Ā© 2019 The Author(s). Completing a construction project on time and within budget is of great importance in the construction industry. To achieve this goal, a construction plan satisfying the time and cost constraints is crucial. While a rich amount of literature on the time-cost trade-off scheduling and time/cost optimization scheduling has been presented, developing a construction plan for the time and cost-constrained construction project has not been fully explored. This study presented a hierarchical task network (HTN) based construction planning model to fill this gap. First of all, a knowledge formalism catering to the HTN planning was provided to accommodate the construction planning knowledge. Then, the planning process was explained in detail, including temporal reasoning used to sequence the construction activities, and backtracking evasion mechanism used to avoid the trouble of backtracking due to inappropriate selection of execution modes for construction activities. Finally, two sets of comparisons based on a fictional construction project were performed, the results of which demonstrate that the time and budget constraints have an impact on the sec-tion of execution modes for construction methods, and the proposed planning model can develop construction plan that satisfies the specified deadline and budget limitations effectively regardless of the existing of backtracking

    PDDL2.1: An Extension to PDDL for Expressing Temporal Planning Domains

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    In recent years research in the planning community has moved increasingly toward s application of planners to realistic problems involving both time and many typ es of resources. For example, interest in planning demonstrated by the space res earch community has inspired work in observation scheduling, planetary rover ex ploration and spacecraft control domains. Other temporal and resource-intensive domains including logistics planning, plant control and manufacturing have also helped to focus the community on the modelling and reasoning issues that must be confronted to make planning technology meet the challenges of application. The International Planning Competitions have acted as an important motivating fo rce behind the progress that has been made in planning since 1998. The third com petition (held in 2002) set the planning community the challenge of handling tim e and numeric resources. This necessitated the development of a modelling langua ge capable of expressing temporal and numeric properties of planning domains. In this paper we describe the language, PDDL2.1, that was used in the competition. We describe the syntax of the language, its formal semantics and the validation of concurrent plans. We observe that PDDL2.1 has considerable modelling power --- exceeding the capabilities of current planning technology --- and presents a number of important challenges to the research community

    PDDL2.1: An Extension to PDDL for Expressing Temporal Planning Domains

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    In recent years research in the planning community has moved increasingly toward s application of planners to realistic problems involving both time and many typ es of resources. For example, interest in planning demonstrated by the space res earch community has inspired work in observation scheduling, planetary rover ex ploration and spacecraft control domains. Other temporal and resource-intensive domains including logistics planning, plant control and manufacturing have also helped to focus the community on the modelling and reasoning issues that must be confronted to make planning technology meet the challenges of application. The International Planning Competitions have acted as an important motivating fo rce behind the progress that has been made in planning since 1998. The third com petition (held in 2002) set the planning community the challenge of handling tim e and numeric resources. This necessitated the development of a modelling langua ge capable of expressing temporal and numeric properties of planning domains. In this paper we describe the language, PDDL2.1, that was used in the competition. We describe the syntax of the language, its formal semantics and the validation of concurrent plans. We observe that PDDL2.1 has considerable modelling power --- exceeding the capabilities of current planning technology --- and presents a number of important challenges to the research community

    Optimal task and motion planning and execution for human-robot multi-agent systems in dynamic environments

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    Combining symbolic and geometric reasoning in multi-agent systems is a challenging task that involves planning, scheduling, and synchronization problems. Existing works overlooked the variability of task duration and geometric feasibility that is intrinsic to these systems because of the interaction between agents and the environment. We propose a combined task and motion planning approach to optimize sequencing, assignment, and execution of tasks under temporal and spatial variability. The framework relies on decoupling tasks and actions, where an action is one possible geometric realization of a symbolic task. At the task level, timeline-based planning deals with temporal constraints, duration variability, and synergic assignment of tasks. At the action level, online motion planning plans for the actual movements dealing with environmental changes. We demonstrate the approach effectiveness in a collaborative manufacturing scenario, in which a robotic arm and a human worker shall assemble a mosaic in the shortest time possible. Compared with existing works, our approach applies to a broader range of applications and reduces the execution time of the process.Comment: 12 pages, 6 figures, accepted for publication on IEEE Transactions on Cybernetics in March 202
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