183 research outputs found
Embedding agents in business applications using enterprise integration patterns
This paper addresses the issue of integrating agents with a variety of
external resources and services, as found in enterprise computing environments.
We propose an approach for interfacing agents and existing message routing and
mediation engines based on the endpoint concept from the enterprise integration
patterns of Hohpe and Woolf. A design for agent endpoints is presented, and an
architecture for connecting the Jason agent platform to the Apache Camel
enterprise integration framework using this type of endpoint is described. The
approach is illustrated by means of a business process use case, and a number
of Camel routes are presented. These demonstrate the benefits of interfacing
agents to external services via a specialised message routing tool that
supports enterprise integration patterns
Monitoring Social Expectations in Second Life
Online virtual worlds such as Second Life provide a rich medium for unstructured human interaction in a shared simulated 3D environment. However, many human interactions take place in a structured social context where participants play particular roles and are subject to expectations governing their behaviour, and current virtual worlds do not provide any support for this type of interaction. There is therefore an opportunity to adapt the tools developed in the MAS community for structured social interactions between software agents (inspired by human society) and adapt these for use with the computer-mediated human communication provided by virtual worlds.
This paper describes the application of one such tool for use with Second Life. A model checker for online monitoring of social expectations defined in temporal logic has been integrated with Second Life, allowing users to be notified when their expectations of others have been fulfilled or violated. Avatar actions in the virtual world are detected by a script, encoded as propositions and sent to the model checker, along with the social expectation rules to be monitored. Notifications of expectation fulfilment and violation are returned to the script to be displayed to the user. This utility of this tool is reliant on the ability of the Linden scripting language (LSL) to detect events of significance in the application domain, and a discussion is presented on how a range of monitored structured social scenarios could be realised despite the limitations of LSL
Obligation Norm Identification in Agent Societies
Most works on norms have investigated how norms are regulated using institutional mechanisms. Very few works have focused on how an agent may infer the norms of a society without the norm being explicitly given to the agent. This paper describes a mechanism for identifying one type of norm, an obligation norm. The Obligation Norm Inference (ONI) algorithm described in this paper makes use of an association rule mining approach to identify obligation norms. Using agent based simulation of a virtual restaurant we demonstrate how an agent can identify the tipping norm. The experiments that we have conducted demonstrate that an agent in the system is able to add, remove and modify norms dynamically. An agent can also flexibly modify the parameters of the system based on whether it is successful in identifying a norm.Norms, Social Norms, Obligations, Norm Identification, Agent-Based Simulation, Simulation of Norms, Artificial Societies, Normative Multi-Agent Systems (NorMAS)
Supporting group plans in the BDI architecture using coordination middleware
This is the full version of a paper published as the following extended abstract:
Supporting Group Plans in the BDI Architecture using Coordination Middleware (Extended Abstract), Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems, 1427-1428, International Foundation for Autonomous Agents and Multiagent Systems, 2016 http://trust.sce.ntu.edu.sg/aamas16/pdfs/p1427.pdfThis paper investigates the use of group plans and goals as programming abstractions that encapsulate the communication needed to coordinate collaborative behaviour. It presents an extension of the BDI agent architecture to include explicit constructs for goals and plans that involve coordinated action by groups of agents. Formal operational semantics for group goals are provided, and an implementation of group plans and goals for the Jason agent platform is described, based on integration with the Zookeeper coordination middleware
Mining International Political Norms from the GDELT Database
Researchers have long been interested in the role that norms can play in
governing agent actions in multi-agent systems. Much work has been done on
formalising normative concepts from human society and adapting them for the
government of open software systems, and on the simulation of normative
processes in human and artificial societies. However, there has been
comparatively little work on applying normative MAS mechanisms to understanding
the norms in human society.
This work investigates this issue in the context of international politics.
Using the GDELT dataset, containing machine-encoded records of international
events extracted from news reports, we extracted bilateral sequences of
inter-country events and applied a Bayesian norm mining mechanism to identify
norms that best explained the observed behaviour. A statistical evaluation
showed that the normative model fitted the data significantly better than a
probabilistic discrete event model.Comment: 16 pages, 2 figures, pre-print for International Workshop on
Coordination, Organizations, Institutions, Norms and Ethics for Governance of
Multi-Agent Systems (COINE), co-located with AAMAS 202
Patient Information Model to Support Population-level Workload Analysis
Evaluation activities in Design Science Research not only verify utility but also scientific rigour and the truth-like value of prescriptive knowledge contributions. Assuming a lack of guidance, evaluation frameworks like the one of Sonnenberg and vom Brocke have been pro- posed prior to evaluating their actual utility to scholars. This research now aims at evaluating how scholars actually apply the framework in practice and their reasoning for doing so. The research-in-progress paper at hand presents preliminary results from a citation analysis. We find an emphasis on ex-post evaluations in artificial settings and a lack of comprehensive detail on ex-ante evaluation activities. The call to accumulate incremental prescriptive knowledge has mostly been ignored and artifact changes are rarely disclosed. Therefore, we question the missing guidance as the sole reason that scholars emphasise building rather than evaluation. We propose to a conduct case study that investigates the reasons behind scholars’ evaluation decisions
Norm violation in online communities -- A study of Stack Overflow comments
Norms are behavioral expectations in communities. Online communities are also
expected to abide by the rules and regulations that are expressed in the code
of conduct of a system. Even though community authorities continuously prompt
their users to follow the regulations, it is observed that hate speech and
abusive language usage are on the rise. In this paper, we quantify and analyze
the patterns of violations of normative behaviour among the users of Stack
Overflow (SO) - a well-known technical question-answer site for professionals
and enthusiast programmers, while posting a comment. Even though the site has
been dedicated to technical problem solving and debugging, hate speech as well
as posting offensive comments make the community "toxic". By identifying and
minimising various patterns of norm violations in different SO communities, the
community would become less toxic and thereby the community can engage more
effectively in its goal of knowledge sharing. Moreover, through automatic
detection of such comments, the authors can be warned by the moderators, so
that it is less likely to be repeated, thereby the reputation of the site and
community can be improved. Based on the comments extracted from two different
data sources on SO, this work first presents a taxonomy of norms that are
violated. Second, it demonstrates the sanctions for certain norm violations.
Third, it proposes a recommendation system that can be used to warn users that
they are about to violate a norm. This can help achieve norm adherence in
online communities.Comment: 16 pages, 8 figures, 2 table
Towards offensive language detection and reduction in four Software Engineering communities
Software Engineering (SE) communities such as Stack Overflow have become
unwelcoming, particularly through members' use of offensive language. Research
has shown that offensive language drives users away from active engagement
within these platforms. This work aims to explore this issue more broadly by
investigating the nature of offensive language in comments posted by users in
four prominent SE platforms - GitHub, Gitter, Slack and Stack Overflow (SO). It
proposes an approach to detect and classify offensive language in SE
communities by adopting natural language processing and deep learning
techniques. Further, a Conflict Reduction System (CRS), which identifies
offence and then suggests what changes could be made to minimize offence has
been proposed. Beyond showing the prevalence of offensive language in over 1
million comments from four different communities which ranges from 0.07% to
0.43%, our results show promise in successful detection and classification of
such language. The CRS system has the potential to drastically reduce manual
moderation efforts to detect and reduce offence in SE communities
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