A planning approach to the automated synthesis of template-based process models

The design-time specification of flexible processes can be time-consuming and error-prone, due to the high number of tasks involved and their context-dependent nature. Such processes frequently suffer from potential interference among their constituents, since resources are usually shared by the process participants and it is difficult to foresee all the potential tasks interactions in advance. Concurrent tasks may not be independent from each other (e.g., they could operate on the same data at the same time), resulting in incorrect outcomes. To tackle these issues, we propose an approach for the automated synthesis of a library of template-based process models that achieve goals in dynamic and partially specified environments. The approach is based on a declarative problem definition and partial-order planning algorithms for template generation. The resulting templates guarantee sound concurrency in the execution of their activities and are reusable in a variety of partially specified contextual environments. As running example, a disaster response scenario is given. The approach is backed by a formal model and has been tested in experiment

What Automated Planning Can Do for Business Process Management

Business 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

The 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

Compositional Reactive Synthesis for Multi-Agent Systems

With growing complexity of systems and guarantees they are required to provide, the need for automated and formal design approaches that can guarantee safety and correctness of the designed system is becoming more evident. To this end, an ambitious goal in system design and control is to automatically synthesize the system from a high-level specification given in a formal language such as linear temporal logic. The goal of this dissertation is to investigate and develop the necessary tools and methods for automated synthesis of controllers from high-level specifications for multi-agent systems. We consider systems where a set of controlled agents react to their environment that includes other uncontrolled, dynamic and potentially adversarial agents. We are particularly interested in studying how the existing structure in systems can be exploited to achieve more efficient synthesis algorithms through compositional reasoning. We explore three different frameworks for compositional synthesis of controllers for multi-agent systems. In the first framework, we decompose the global specification into local ones, we then refine the local specifications until they become realizable, and we show that under certain conditions, the strategies synthesized for the local specifications guarantee the satisfaction of the global specification. In the second framework, we show how parametric and reactive controllers can be specified and synthesized, and how they can be automatically composed to enforce a high-level objective. Finally, in the third framework, we focus on a special but practically useful class of multi-agent systems, and show how by taking advantage of the structure in the system and its objective we can achieve significantly better scalability and can solve problems where the centralized synthesis algorithm is infeasible

Adaptive Process Management in Cyber-Physical Domains

The increasing application of process-oriented approaches in new challenging cyber-physical domains beyond business computing (e.g., personalized healthcare, emergency management, factories of the future, home automation, etc.) has led to reconsider the level of flexibility and support required to manage complex processes in such domains. A cyber-physical domain is characterized by the presence of a cyber-physical system coordinating heterogeneous ICT components (PCs, smartphones, sensors, actuators) and involving real world entities (humans, machines, agents, robots, etc.) that perform complex tasks in the “physical” real world to achieve a common goal. The physical world, however, is not entirely predictable, and processes enacted in cyber-physical domains must be robust to unexpected conditions and adaptable to unanticipated exceptions. This demands a more flexible approach in process design and enactment, recognizing that in real-world environments it is not adequate to assume that all possible recovery activities can be predefined for dealing with the exceptions that can ensue. In this chapter, we tackle the above issue and we propose a general approach, a concrete framework and a process management system implementation, called SmartPM, for automatically adapting processes enacted in cyber-physical domains in case of unanticipated exceptions and exogenous events. The adaptation mechanism provided by SmartPM is based on declarative task specifications, execution monitoring for detecting failures and context changes at run-time, and automated planning techniques to self-repair the running process, without requiring to predefine any specific adaptation policy or exception handler at design-time

Exploiting More Binaries by Using Planning to Assemble ROP Attacks

Return oriented programming (ROP) attacks have been studied for many years, but they are usually still constructed manually. The existing tools to synthesize ROP exploits automatically, such as ROPGadget and angrop, are very limited by their ad-hoc design: they rely on matching fixed patterns and assembling gadgets in fixed ways. We propose a new method, PEACE, that uses symbolic execution and partial-order planning to assemble gadgets more flexibly. Our method incrementally selects gadgets to address a need in the partially-constructed exploit, and infers ordering constraints over those gadgets based on their effects. This approach enables PEACE to create exploits for many more binaries than existing tools. By creating a more flexible and powerful ROP attack generation tool, we hope to raise awareness of how much code is vulnerabl

Working Notes from the 1992 AAAI Workshop on Automating Software Design. Theme: Domain Specific Software Design

The goal of this workshop is to identify different architectural approaches to building domain-specific software design systems and to explore issues unique to domain-specific (vs. general-purpose) software design. Some general issues that cut across the particular software design domain include: (1) knowledge representation, acquisition, and maintenance; (2) specialized software design techniques; and (3) user interaction and user interface