PISAGOR: a proactive software agent for monitoring interactions

Özgür Kafalı; Pınar Yolum

doi:10.1007/s10115-015-0848-1

PISAGOR: a proactive software agent for monitoring interactions

Özgür Kafalı^*, Pınar Yolum

^*Corresponding author for this work

Dept of Information and Computing Sciences

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

E-commerce has become an integral part of everyday life. Many e-commerce systems enable users to browse products, place orders, and track deliveries online. However, these interactions is time-consuming, especially if they do not proceed as expected. Instead of a human user, software can offer automated support to monitor e-commerce transactions to ensure that they are completed by the businesses as planned. Accordingly, this paper studies methods to develop a software agent for monitoring its users’ interactions with businesses (PISAGOR). The interactions are represented as commitments, which have been extensively studied in multiagent systems. With a commitment-based specification at hand, the agent knows what the meaning of its interactions are and can therefore reason over its actions. The reasoning is accompanied with the as-good-as relation that compares the agent’s current state with its expectations from a transaction. This enables PISAGOR to decide whether the transaction is progressing as expected. Moreover, we propose operational rules for the agent to create expectations based on its commitments and check its progress toward them. We demonstrate via a case study how PISAGOR can detect if a user’s interactions are not progressing well and identify a problem for the user to take action.

Original language	English
Pages (from-to)	215-239
Number of pages	25
Journal	Knowledge and Information Systems
Volume	47
Issue number	1
DOIs	https://doi.org/10.1007/s10115-015-0848-1
Publication status	Published - 1 Apr 2016

Bibliographical note

Funding Information:
We thank the anonymous reviewers for their useful comments and suggestions. Most of this work was done while ÃzgÃ¼r Kafal? was doing research in Bogazici University and Royal Holloway, University of London. This research is supported by Bogazici University Research Fund under Grant BAP13A01P2 and the Scientific and Technological Research Council of Turkey (TUBITAK) under Grant 113E543.

Funding Information:
We thank the anonymous reviewers for their useful comments and suggestions. Most of this work was done while Özgür Kafalı was doing research in Bogazici University and Royal Holloway, University of London. This research is supported by Bogazici University Research Fund under Grant BAP13A01P2 and the Scientific and Technological Research Council of Turkey (TUBITAK) under Grant 113E543.

Publisher Copyright:
© 2015, Springer-Verlag London.

Funding

We thank the anonymous reviewers for their useful comments and suggestions. Most of this work was done while ÃzgÃ¼r Kafal? was doing research in Bogazici University and Royal Holloway, University of London. This research is supported by Bogazici University Research Fund under Grant BAP13A01P2 and the Scientific and Technological Research Council of Turkey (TUBITAK) under Grant 113E543. We thank the anonymous reviewers for their useful comments and suggestions. Most of this work was done while Özgür Kafalı was doing research in Bogazici University and Royal Holloway, University of London. This research is supported by Bogazici University Research Fund under Grant BAP13A01P2 and the Scientific and Technological Research Council of Turkey (TUBITAK) under Grant 113E543.

Keywords

Agent-based commerce
Commitments
Expectations
Multiagent systems

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10.1007/s10115-015-0848-1

Cite this

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title = "PISAGOR: a proactive software agent for monitoring interactions",

abstract = "E-commerce has become an integral part of everyday life. Many e-commerce systems enable users to browse products, place orders, and track deliveries online. However, these interactions is time-consuming, especially if they do not proceed as expected. Instead of a human user, software can offer automated support to monitor e-commerce transactions to ensure that they are completed by the businesses as planned. Accordingly, this paper studies methods to develop a software agent for monitoring its users{\textquoteright} interactions with businesses (PISAGOR). The interactions are represented as commitments, which have been extensively studied in multiagent systems. With a commitment-based specification at hand, the agent knows what the meaning of its interactions are and can therefore reason over its actions. The reasoning is accompanied with the as-good-as relation that compares the agent{\textquoteright}s current state with its expectations from a transaction. This enables PISAGOR to decide whether the transaction is progressing as expected. Moreover, we propose operational rules for the agent to create expectations based on its commitments and check its progress toward them. We demonstrate via a case study how PISAGOR can detect if a user{\textquoteright}s interactions are not progressing well and identify a problem for the user to take action.",

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N2 - E-commerce has become an integral part of everyday life. Many e-commerce systems enable users to browse products, place orders, and track deliveries online. However, these interactions is time-consuming, especially if they do not proceed as expected. Instead of a human user, software can offer automated support to monitor e-commerce transactions to ensure that they are completed by the businesses as planned. Accordingly, this paper studies methods to develop a software agent for monitoring its users’ interactions with businesses (PISAGOR). The interactions are represented as commitments, which have been extensively studied in multiagent systems. With a commitment-based specification at hand, the agent knows what the meaning of its interactions are and can therefore reason over its actions. The reasoning is accompanied with the as-good-as relation that compares the agent’s current state with its expectations from a transaction. This enables PISAGOR to decide whether the transaction is progressing as expected. Moreover, we propose operational rules for the agent to create expectations based on its commitments and check its progress toward them. We demonstrate via a case study how PISAGOR can detect if a user’s interactions are not progressing well and identify a problem for the user to take action.

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PISAGOR: a proactive software agent for monitoring interactions

Abstract

Bibliographical note

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Keywords

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