Anup K. Kalia

Monitoring Commitments in People-Driven Service Engagements

People-driven service engagements involve communication over channels such as chat and email. Such engagements should be understood at the level of the commitments that the participants create and manipulate. Doing so provides a grounding for the communications and yields a business-level accounting of the progress of a service engagement. Existing work on commitment-based service engagements is limited to design-time model creation and verification. In contrast, we present a novel approach for capturing commitment-based engagements that are created dynamically in conversations. We monitor commitments identifying their creation, delegation, completion, or cancellation in the conversations. We have developed a prototype and evaluated it on real-world chat and email datasets. Our prototype captures commitments with a high F-measure of 90% in emails (Enron email corpus) and 80% in chats (HP IT support chat dataset) and provides promising results for capturing additional commitment operations.

Behind the Curtain: Service Selection via Trust in Composite Services

Service selection, where some of the services are accessed indirectly as constituents of composite services, is difficult for the following reasons: (1) the interpretation of service qualities is subjective; (2) evidence must be combined from multiple sources; (3) service profiles change dynamically; and (4) constituent services may be only partially observable behind composite services. We propose an approach where we map service qualities to a common probabilistic trust metric. Whereas current trust approaches estimate the trustworthiness of a composite service based on a fully observable and static setting, we propose a statistical approach built on expectation maximized over a finite mixture model. Our experiments show that our approach can dynamically punish or reward the constituents of composite services while making only partial observations.

Muon: designing multiagent communication protocols from interaction scenarios

Designing a suitable communication protocol is a key challenge in engineering a multiagent system. This paper proposes Muon, an approach that begins from representative samples of interactions or scenarios. Muon identifies key semantic structures and patterns based on (social) commitments to formally analyze the scenarios and offers a methodology for designing protocols that would meet stakeholder needs. Interestingly, Muon applies its formal representations to suggest ways to identify additional scenarios needed to address exceptions arising in the interactions. This paper contributes (1) a conceptual model of message types and causal relationships among them as a foundation for developing commitment-based communication protocols; (2) a robust, reusable characterization of semantic structures reflecting the above model; (3) a mapping from an annotated scenario to causally related interactions; and (4) a methodology to synthesize specifications of communication protocols. This paper reports on an empirical evaluation involving developers creating protocols from two real-life cases.

Classifying sanctions and designing a conceptual sanctioning process model for socio-technical systems

We understand a socio-technical system (STS) as a cyber-physical system in which two or more autonomous parties interact via or about technical elements, including the parties’ resources and actions. As information technology begins to pervade every corner of human life, STSs are becoming ever more common, and the challenge of governing STSs is becoming increasingly important. We advocate a normative basis for governance, wherein norms represent the standards of correct behaviour that each party in an STS expects from others. A major benefit of focussing on norms is that they provide a socially realistic view of interaction among autonomous parties that abstracts low-level implementation details. Overlaid on norms is the notion of a sanction as a negative or positive reaction to potentially any violation of or compliance with an expectation. Although norms have been well studied as regards governance for STSs, sanctions have not. Our understanding and usage of norms is inadequate for the purposes of governance unless we incorporate a comprehensive representation of sanctions. We address the aforementioned gap by proposing (i) a sanction typology that reflects the relevant features of sanctions, and (ii) a conceptual sanctioning process model providing a functional structure for sanctioning in STS. We demonstrate our contributions via a motivating scenario from the domain of renewable energy trading.

Engineering Service Engagements via Commitments

A service engagement describes how two or more independent parties interact with each other. Traditional approaches specify these interactions as message sequence charts (MSCs), hiding underlying business relationships and, consequently, complicating modification. Comma is a commitment-based approach that produces a business model drawn from an extensible pattern library and yields flexible MSCs. An empirical study shows that models produced via Comma yield superior flexibility, are comprehensible to others, and take less time and effort to produce. The Web extra presents the claims regarding Commas effectiveness as a set of alternative hypotheses, as well as the complete list of MSCs developed via both traditional and Comma approaches.

Güven: estimating trust from communications

The extent to which an agent trusts another naturally depends on the outcomes of their interactions. Previous computational approaches have treated the outcomes in a domain-specific way. Specifically, these approaches focus on the mathematical aspect and assume that a positive or negative experience can be identified without showing how to ground the experiences in real-world interactions, such as emails and chats. We propose Güven, an approach that relates trust to the domain-independent notion of commitments. We consider commitments since commitment outcomes can be associated with experiences and a large body of works exist on commitments that include commitment representation and semantics. Also, recent research shows that commitments can be extracted from interactions, such as emails and chats. Thus, we posit Güven can provide an useful basis to infer trust between agents from their interactions.To evaluate Güven, we conducted empirical studies of two decision contexts. First, subjects read emails extracted from the Enron dataset (and augmented with some synthetic emails for completeness), and estimated trust between each pair of communicating agents. Second, the subjects played the Colored Trails game, estimating trust in their opponents. Güven incorporates a probabilistic model for trust based on commitment outcomes; we show how to train its parameters for each subject based on the subject’s assessments. The results are promising, though imperfect. Our main contribution is to launch a research program into computing trust based on a semantically well-founded account of interpersonal interactions.

A Collaborative Approach to Predicting Service Price for QoS-Aware Service Selection

In QoS-aware service selection, a service requester seeks to maximize its utility by selecting a service provider that charges the lowest service price while meeting the requesters QoS requirements. In existing selection approaches, a service requester focuses on finding providers based on their QoS and thereby ignores their service prices that could change with their QoS. High QoS may provide more benefits, but may require a high service price. As a result, the highest QoS may not produce the maximum utility. A service requester and candidate service providers have a conflicting interest over service prices. Since a provider would not reveal its minimum acceptabl price, it is important for a requester to predict the minimum price for a service that meets its QoS requirements. We propose a collaborative approach to predicting a providers minimum price for a desired QoS based on prior usage experience. The experimental results show our approach can find the optimal service providers efficiently and effectively.

Combining Practical and Dialectical Commitments for Service Engagements

We understand a service engagement as a form of collaboration arising in a sociotechnical system (STS). Although STSs are fruitfully modeled using normative abstractions such as commitments, a conventional (practical) commitment can capture only part of the story, namely, a debtor’s promise to the creditor to bring about the consequent if the antecedent holds. In contrast, in a dialectical commitment, which we highlight, a debtor asserts to the creditor that the consequent is true if the antecedent is. For example, a customer may dialectically commit to a seller that the product she received is damaged but may not practically commit to damaging the product. We introduce a novel bipartite operationalization of dialectical commitments that separates their objective and subjective aspects and thus avoids the problems arising if we merely treat dialectical like practical commitments. We express that operationalization in temporal logic, developing a verification tool based on NuSMV, a well-known model-checker, to verify if the participants’ interactions comply with the participants’ dialectical commitments. We present a set of modeling patterns that incorporate both practical and dialectical commitments. We validate our proposal using a real-world scenario of contradictory medical diagnoses by different specialists.

Determining Team Hierarchy from Broadcast Communications

Broadcast chat messages among team members in an organization can be used to evaluate team coordination and performance. Intuitively, a well-coordinated team should reflect the team hierarchy, which would indicate that team members assigned with particular roles are performing their jobs effectively. Existing approaches to identify hierarchy are limited to data from where graphs can be extracted easily. We contribute a novel approach that takes as input broadcast messages, extracts communication patterns—as well as semantic, communication, and social features—and outputs an organizational hierarchy. We evaluate our approach using a dataset of broadcast chat communications from a large-scale Army exercise for which ground truth is available. We further validate our approach on the Enron corpus of corporate email.

Estimating trust from agents' interactions via commitments

How an agent trusts another naturally depends on the outcomes of their interactions. Previous approaches have treated the outcomes in a domain-specific way. We propose an approach relating trust to the domain-independent notion of commitments. We conduct an empirical study to evaluate our approach, in which subjects read emails extracted from the Enron dataset (augmented with some synthetic emails for completeness), and estimate trust between each pair of communicating participants. We propose a probabilistic model for trust based on commitment outcomes and show how to train its parameters for each subject based on the subjects trust assessments. The results are promising, though imperfect. Our main contribution is to launch a research program into computing trust based on a semantically well-founded account of agent interactions.