Aditya K. Ghose

Auditing Business Process Compliance

Compliance issues impose significant management and reporting requirements upon organizations. We present an approach to enhance business process modeling notations with the capability to detect and resolve many broad compliance related issues. We provide a semantic characterization of a minimal revision strategy that helps us obtain compliant process models from models that might be initially non-compliant, in a manner that accommodates the structural and semantic dimensions of parsimoniously annotated process models. We also provide a heuristic approach to compliance resolution using a notion of compliance patterns. This allows us to partially automate compliance resolution, leading to reduced levels of analyst involvement and improved decision support.

Agent Computing and Multi-Agent Systems

Existence of Risk Strategy Equilibrium in Games Having No Pure Strategy Nash Equilibrium.- Multiagent Planning with Trembling-Hand Perfect Equilibrium in Multiagent POMDPs.- MAGEFRAME: A Modular Agent Framework to Support Various Communication Schemas Based on a Self-embedding Algorithm.- Using Multiagent System to Build Structural Earth Model.- Agent-Supported Protein Structure Similarity Searching.- Merging Roles in Coordination and in Agent Deliberation.- Planning Actions with Social Consequences.- Layered Cooperation of Macro Agents and Micro Agents in Cooperative Active Contour Model.- Contextual Agent Deliberation in Defeasible Logic.- Real-Time Moving Target Search.- Formalizing Excusableness of Failures in Multi-Agent Systems.- Design and Implementation of Security Mechanisms for a Hierarchical Community-Based Multi-Agent System.- A Need for Biologically Inspired Architectural Description: The Agent Ontogenesis Case.- Multi-Agent Based Web Search with Heterogeneous Semantics.- Reasoning about Norms, Obligations, Time and Agents.- An Agent Modeling Method Based on Scenario Rehearsal for Multiagent Simulation.- Fast Partial Reallocation in Combinatorial Auctions for Iterative Resource Allocation.- Deliberation Process in a BDI Model with Bayesian Networks.- An Asymmetric Protocol for Argumentation Games in Defeasible Logic.- On the Design of Interface Agents for a DRT Transportation System.- Supporting Requirements Analysis in Tropos: A Planning-Based Approach.- Towards Method Engineering for Multi-Agent Systems: A Validation of a Generic MAS Metamodel.- Entrainment in Human-Agent Text Communication.- A Driver Modeling Methodology Using Hypothetical Reasoning for Multiagent Traffic Simulation.- Analysis of Pedestrian Navigation Using Cellular Phones.- Identifying Structural Changes in Networks Generated from Agent-Based Social Simulation Models.- Multi-agent Simulation of Linguistic Processes: A NEPs Perspective.- A 3D Conversational Agent for Presenting Digital Information for Deaf People.- Multiagent-Based Defensive Strategy System for Military Simulation.- Achieving DRBAC Authorization in Multi-trust Domains with MAS Architecture and PMI.- When and How to Smile: Emotional Expression for 3D Conversational Agents.- GAMA: An Environment for Implementing and Running Spatially Explicit Multi-agent Simulations.- Multi-agent Based Incineration Process Control System with Qualitative Model.- Engineering Adaptive Multi-Agent Systems with ODAM Methodology.- Integrating Agent Technology and SIP Technology to Develop Telecommunication Applications with JadexT.- A Generic Distributed Algorithm for Computing by Random Mobile Agents.- Coalition Structure Generation in Task-Based Settings Based on Cardinality Structure.- A Specialised Architecture for Embedding Trust Evaluation Capabilities in Intelligent Mobile Agents.- Reasoning with Levels of Modalities in BDI Logic.- A Distributed Computational Model for Mobile Agents.- Belief-Based Stability in Non-transferable Utility Coalition Formation.- Deja Vu: Social Network Agents for Personal Impression Management.- Agent Dialogue as Partial Argumentation and Its Fixpoint Semantics.- Developing Knowledge Models for Multi-agent Mediator Systems.- A Game Theoretic Approach for Deploying Intrusion Detection Agent.- Double Token-Ring and Region-Tree Based Group Communication Mechanism for Mobile Agent.- Towards Culturally-Situated Agent Which Can Detect Cultural Differences.- Ontology-Based Emotion System for Digital Environment.- An Agent Approach for Distributed Job-Shop Scheduling.

Relating business process models to goal-oriented requirements models in KAOS

Business Process Management (BPM) has many anticipated benefits including accelerated process improvement, at the operational level, with the use of highly configurable and adaptive “process aware” information systems [1] [2]. The facility for improved agility fosters the need for continual measurement and control of business processes to assess and manage their effective evolution, in-line with organizational objectives. This paper proposes the GoalBPM methodology for relating business process models (modeled using BPMN) to high-level stakeholder goals (modeled using KAOS). We propose informal (manual) techniques (with likely future formalism) for establishing and verifying this relationship, even in dynamic environments where essential alterations to organizational goals and/or process constantly emerge.

Process SEER: A Tool for Semantic Effect Annotation of Business Process Models

A key challenge in devising solutions to a range of problems associated with business process management: process life cycle management, compliance management, enterprise process architectures etc. is the problem of identifying process semantics. The current industry standard business process modeling notation, BPMN, provides little by way of semantic description of the effects of a process (beyond what can be conveyed via the nomenclature of tasks and the decision conditions associated with gateways). In this paper, we describe the conceptual underpinnings, design, implementation and evaluation of the ProcessSEER tool that supports several strategies for obtaining semantic effect descriptions of BPMN process models, without imposing an overly onerous burden of using formal specification on the analyst. The tool requires analysts to describe the immediate effects of each task. These are then accumulated in an automated fashion to obtain cumulative effect annotations for each task in a process. The tool leverages domain ontologies wherever they are available. The tool permits the analyst to specify immediate effect annotations in a practitioner-accessible controlled natural language, which enables formal specification using a limited repertoire of natural language sentence formats. The tool also leverages semantic web services in a similar fashion.

Process Discovery from Model and Text Artefacts

Modeling is an important and time consuming part of the business process management life-cycle. An analyst reviews existing documentation and queries relevant domain experts to construct both mental and concrete models of the domain. To aid this exercise, we propose the Rapid Business Process Discovery (R-BPD) framework and prototype tool that can query heterogeneous information resources (e.g. corporate documentation, web-content, code e.t.c.) and rapidly constructproto-models to be incrementally adjusted to correctness by an analyst. This constitutes a departure from building and constructing models toward just editing them. We believe this rapid mixed-initiative modeling will increase analyst productivity by significant orders of magnitude over traditional approaches. Furthermore, the possibility of using the approach in distributed and real-time settings seems appealing and may help in significantly improving the quality of the models being developed w.r.t. being consistent, complete, and concise.

An Ontology-Based Sentiment Classification Methodology for Online Consumer Reviews

This paper presents a method of ontology-based sentiment classification to classify and analyse online product reviews of consumers. We implement and experiment with a support vector machines text classification approach based on a lexical variable ontology. After testing, it could be demonstrated that the proposed method can provide more effectiveness for sentiment classification based on text content.

A Framework for Reasoning about Requirements Evolution

We present a logical framework for modelling and reasoning about requirements evolution in the construction of information systems. Our framework represents a requirements model as a theory of some nonmonotonic logic, while requirements evolution is modelled as a mapping between such theories, based on the AGM logic of belief change [1]. We demonstrate our ideas by using the THEORIST system for nonmonotonic reasoning. Moreover we examine the Telos system for requirements modelling in terms of our framework, and we identify some obvious shortcomings and propose possible solutions. We argue that our framework provides a powerful tool both for analysing and comparing existing systems and for developing automated systems to support requirements evolution.

Social choice theory, belief merging, and strategy-proofness

Intelligent agents have to be able to merge informational inputs received from different sources in a coherent and rational way. Several proposals have been made for information merging in which it is possible to encode the preferences of sources [5,4,19,24,25,1]. Information merging has much in common with social choice theory, which aims to define operations reflecting the preferences of a society from the individual preferences of the members of the society. Given this connection, frameworks for information merging should provide satisfactory resolutions of problems raised in social choice theory. We investigate the link between the merging of epistemic states and some results in social choice theory. This is achieved by providing a consistent set of properties-akin to those used in Arrows theorem [2]-for merging. It is shown that in this framework there is no Arrow-like impossibility result. By extending this to a consistent framework which includes properties corresponding to the notion of being strategy-proof, we show that results due to Gibbard and Satterthwaite [13,31,32] and others [6,3] do not hold in merging frameworks.

Verifying Semantic Business Process Models in Inter-operation

Process inter-operation is characterized as cooperative interactions among loosely coupled autonomous constituents to adaptively fulfill system-wide purpose. Issues of inconsistency can be anticipated in inter-operating processes given their independent management and design. To reduce inconsistency (that may contribute to failures) effective methods for statically verifying behavioral interoperability are required. This paper contributes a method for practical, semantic verification of interoperating processes (as represented with BPMN models). We provide methods to evaluate consistency during process design where annotation of the immediate effect of tasks and sub-processes has been provided. Furthermore, some guidelines are defined against common models of inter-operation for scoping traceability to possible causes of inconsistency. This supports subsequent resolution efforts.

Strategic alignment of business processes

Strategic alignment is a mechanism by which an organization can visualize the relationship between its business processes and strategies. It enables organizational decision makers to collect meaningful insights based on their current processes. Currently it is difficult to show the sustainability of an organization and to determine an optimal set of processes that are required for realizing strategies. Further, there is not a general framework for strategic alignment that can ease this problem. In this article, we propose such a general framework for strategic alignment, which helps develop a clear understanding of the relationships between strategies and business processes. The framework gives organizations an understanding of the relationship between a set of processes and the realization of a set of strategies; it also shows the optimal set of processes that can achieve these strategies.