1,721,107 research outputs found
What Automated Planning Can Do for Business Process Management
Full text linkBusiness Process Management (BPM) is a central element of today organizations. Despite over the years its main focus has been the support of processes in highly controlled domains, nowadays many domains of interest to the BPM community are characterized by ever-changing requirements, unpredictable environments and increasing amounts of data that influence the execution of process instances. Under such dynamic conditions, BPM systems must increase their level of automation to provide the reactivity and flexibility necessary for process management. On the other hand, the Artificial Intelligence (AI) community has concentrated its efforts on investigating dynamic domains that involve active control of computational entities and physical devices (e.g., robots, software agents, etc.). In this context, Automated Planning, which is one of the oldest areas in AI, is conceived as a model-based approach to synthesize autonomous behaviours in automated way from a model. In this paper, we discuss how automated planning techniques can be leveraged to enable new levels of automation and support for business processing, and we show some concrete examples of their successful application to the different stages of the BPM life cycle
SmartPM: automatic adaptation of dynamic processes at run-time
Full text linkThe research activity outlined in this thesis is devoted to define a general approach, a concrete architecture and a prototype Process Management System (PMS) for the automated adaptation of dynamic processes at run-time, on the basis of a declarative specification of process tasks and relying on well-established reasoning about actions and planning techniques. The purpose is to demonstrate that the combination of procedural and imperative models with declarative elements, along with the exploitation of techniques from the field of artificial intelligence (AI), such as Situation Calculus, IndiGolog and automated planning, can increase the ability of existing PMSs of supporting dynamic processes. To this end, a prototype PMS named SmartPM, which is specifically tailored for supporting collaborative work of process participants during pervasive scenarios, has been developed. The adaptation mechanism deployed on SmartPM is based on execution monitoring for detecting failures at run-time, which does not require the definition of the adaptation strategy in the process itself (as most of the current approaches do), and on automatic planning techniques for the synthesis of the recovery procedure
Towards a Planning-Based Approach to the Automated Design of Chemical Processes
No full textThe design of chemical processes is a central problem in organic
chemistry. A chemical process is a sequence of chemical reactions capable of producing a target compound from some starting stage molecules. The manual specification of such processes can be time-consuming and error-prone, due to the high number of reactions involved and their complex chemical conditions. To tackle this issue, we propose a planning-based approach and a framework for the automated design of chemical processes. Specifically, we argue that this problem can be reduced to a planning problem in Artificial Intelligence. To this end, we adapt the situation calculus and PDDL to the task of modeling molecules and capturing semantics of generic chemical reactions, and we conduct experimental study including empirical assessment of a PROLOG planner and two state-of-the-art
planners on a set of benchmark problems
Knowledge-intensive Processes: An Overview of Contemporary Approaches
No full textEngineering of knowledge-intensive processes is far from being mastered. Processes are defined knowledge-intensive when people/agents carry them out in a fair degree of "uncertainty", where the uncertainty depends on different factors, such as the high number of tasks to be represented, their unpredictable nature, or their dependency on the scenario. In the worst case, there is no pre-defined view of the knowledge-intensive process, and tasks are mainly discovered as the process unfolds. In this work, starting from three different real scenarios, we present a critical comparative analysis of the existing approaches used for supporting knowledge-intensive processes, and we discuss some recent research techniques that may complement or extend the existing state of the art
Organic Synthesis as Artificial Intelligence Planning
No full textWe explore advantages that can be gained from using expressive logic
languages for semantic modelling of chemical reactions. First, we present a novel approach for logical representation of notions in organic chemistry, as well as for reasoning about generic chemical reactions. Subsequently, using this new semantic modeling of reactions, we explore what reasoning problems can be solved.
We focus on solving organic chemistry synthesis problems, where the goal is to synthesize the target molecule from a set of starting stage molecules. We argue that this problem can be reduced to a planning problem in Artificial Intelligence. We conduct experimental study including empirical assessment of a PROLOG planner and two state-of-the-art planners. We investigate if they are capable of solving a set of instances of the organic synthesis problem. We report numerical
data from our study and do comparative analysis of the planners. The novelty of our work is in using state-of-the art planners for solving the organic synthesis problem. The significance of our work is in methodology that we developed and in showing that expressive logical language can be useful for semantic modeling
Collaboration On-the-field: Suggestions and Beyond
No full textIn disaster scenarios, emergency operators/first responders need to collaborate in order to reach a common goal. The use of mobile devices and applications in these scenarios is very valuable as they can improve collaboration, coordination, and communication amongst team members. But there are also risks involved while using these mobile applications, e.g., decreasing of performance. Most of the tasks are highly critical and time demanding, e.g., saving minutes could result in saving people's life. Therefore, it is unacceptable to use systems that lack proper interaction principles. In this paper, we provide some suggestions, in the form of lessons learned and/or hints for possible future research activities, on how to effectively support on-the-field collaboration of emergency operators. Such suggestions are based on the authors' experience in a recently concluded successful research project on the use of mobile devices for supporting first responders
An Adaptive Process Management System Implementation Based on Situatio Calculus, Indigolog and Classical Planning
No full textIn this paper, we introduce an adaptive Process Management System implementation that combines business process execution monitoring, unanticipated exception detection and automated resolution strategies leveraging on well-established formalisms developed for reasoning about actions in Artificial Intelligence, including the situation calculus, IndiGolog and classical planning. Such formalisms provide a natural framework for the formal specification of explicit mechanisms to model world changes and responding to anomalous situations, exceptions, exogenous events in an automated way during process execution
Knowledge-Intensive Processes: Characteristics, Requirements and Analysis of Contemporary Approaches
Full text linkEngineering of knowledge-intensive processes (KiPs) is far from being mastered, since they are genuinely knowledge- and data-centric, and require substantial flexibility, at both design- and run-time. In this work, starting from a scientific literature analysis in the area of KiPs and from three real-world domains and application scenarios, we provide a precise characterization of KiPs. Furthermore, we devise some general requirements related to KiPs management and execution. Such requirements contribute to the definition of an evaluation framework to assess current system support for KiPs. To this end, we present a critical analysis on a number of existing process-oriented approaches by discussing their efficacy against the requirements
Continuous Planning for Solving Business Process Adaptivity
No full textProcess Management Systems (PMSs, aka Workflow Management Systems- WfMSs) are currently more and more used as a supporting tool to coordinate the enactment of processes. In real world scenarios, the environment may change in unexpected ways so as to prevent a process from being successfully carried out. In order to cope with these anomalous situations, a PMS should automatically adapt the process without completely replacing it. In this paper, we propose a technique, based on continuous planning, to automatically cope with unexpected changes, in order to modify only those parts of the process that need to be changed/adapted and keeping other parts stable. We also provide a running example that shows the practical applicability of the approach
Towards a Goal-oriented Framework for the Automatic Synthesis of Underspecified Activities in Dynamic Processes
No full textIt is difficult to produce a detailed model of a dynamic process ahead of time. Such processes may include some underspecified activities whose exact definition is not yet known at design-time, and may not be known until the time that an instance of the process has started execution, due to their context-dependent nature. In this paper, we propose a goal-oriented framework to model and specify dynamic processes that allows us to dynamically select and/or synthesize automatically at run-time the content of underspecified activities
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