Publications
435 results found
Morge M, McGinnis J, Bromuri S, et al., 2013, Argumentative Agents for Service-Oriented Computing, Pages: 217-255, ISBN: 9783642333224
We propose an argumentation-based agent model that supports service and partner selection in service-oriented computing settings. In this model, argumentation is also used to help agents resolve conflicts between themselves, whenever negotiation is required for the provision of complex services. The model relies upon an argumentation framework that is used in a modular architecture where Knowledge, Goals, Decisions and Priorities are manipulated by three specialized modules dealing with decision making, communication and negotiation.We formulate a distributed e-procurement process to illustrate how our agents select services and partners and can negotiate with one another. © Springer-Verlag Berlin Heidelberg 2013.
Evripidou V, Toni F, 2013, Quaestio-it.com: From debates towards trustworthy answers (extended abstract)
Information sharing between online users has altered the way we seek and find information. Users have at their disposal a wide range of tools for exchanging opinions and engaging into discussions. This creates a large amount of user generated information that can often be misleading, false or even malicious. We demonstrate a question-and-answer web application, based on Computational Argumentation, that offers debating infrastructure for opinion exchanges. It empowers users to organically determine trustworthy answers through their feedback which takes the form of voting and posting attacking or supporting arguments. © 2013 Springer-Verlag.
Schulz C, Sergot M, Toni F, 2013, Argumentation-based answer set justification
We suggest a method for justifying why a literal is or is notcontained in the answer set of a logic program. This methodmakes use of argumentation theory, more precisely of stableASPIC+ extensions. We describe a way to translate a logicprogram into an ASPIC+ argumentation theory and investigate the relation between answer sets of the logic programand stable extensions of the translated ASPIC+ argumentation theory. The structure of ASPIC+ arguments with respectto a stable extension is then used for the justification of literalswith respect to an answer set. We also present an implementation of our justification method which displays justificationsas graphs.
Kakas A, Toni F, Mancarella P, 2013, Argumentation for propositional logic and nonmonotonic reasoning
Argumentation has played a significant role in understanding and unifying under a common framework different formsof defeasible reasoning in AI. Argumentation is also close tothe original inception of logic as a framework for formalizinghuman argumentation and debate. In this context, the purpose of this paper is twofold: to draw a formal connection between argumentation and classical reasoning (in the form ofPropositional Logic) and link this to support defeasible, NonMonotonic Reasoning in AI. To this effect, we propose Argumentation Logic and show properties and extensions thereof.
Modgil S, Toni F, Bex F, et al., 2013, The added value of argumentation, Agreement Technologies, Pages: 357-403, ISBN: 9789400755826
We discuss the value of argumentation in reaching agreements, based on its capability for dealing with conflicts and uncertainty. Logic-based models of argumentation have recently emerged as a key topic within Artificial Intelligence. Key reasons for the success of these models is that they are akin to human models of reasoning and debate, and their generalisation to frameworks for modelling dialogues. They therefore have the potential for bridging between human and machine reasoning in the presence of uncertainty and conflict. We provide an overview of a number of examples that bear witness to this potential, and that illustrate the added value of argumentation. These examples amount to methods and techniques for argumentation to aid machine reasoning (e.g. in the form of machine learning and belief functions) on the one hand and methods and techniques for argumentation to aid human reasoning (e.g. for various forms of decision making and deliberation and for the Web) on the other. We also identify a number of open challenges if this potential is to be realised, and in particular the need for benchmark libraries.
Carstens L, Toni F, 2013, Enhancing sentiment extraction from text by means of arguments
Sentiment Analysis is concerned with (1) differentiating opinionated text from factual text and, in the case of opinionated text, (2) determine its polarity. With this paper, we address problem (1) and present A-SVM (Argument enhanced Support Vector Machines), a multimodal system that focuses on the discrimination of opinionated text from non-opinionated text with the help of (i) Support Vector Machines (SVM) and (ii) arguments, acquired by means of a user feedback mechanism, and used to improve the SVM classiffications. We have used a prototype to investigate the validity of approaching Sentiment Analysis in this multi faceted manner by comparing straightforward Machine Learning techniques with our multimodal system architecture. All evaluations were executed using a purpose-built corpus of annotated text and A-SVM's classiffication performance was compared to that of SVM. The classiffication of a test set of approximately 4,500 n-grams yielded an increase in classiffication precision of 5.6%.
Modgil S, Toni F, Bex F, et al., 2013, The Added Value of Argumentation, Law, Governance and Technology Series, Pages: 357-403
We discuss the value of argumentation in reaching agreements, based on its capability for dealing with conflicts and uncertainty. Logic-based models of argumentation have recently emerged as a key topic within Artificial Intelligence. Key reasons for the success of these models is that they are akin to human models of reasoning and debate, and their generalisation to frameworks for modelling dialogues. They therefore have the potential for bridging between human and machine reasoning in the presence of uncertainty and conflict. We provide an overview of a number of examples that bear witness to this potential, and that illustrate the added value of argumentation. These examples amount to methods and techniques for argumentation to aid machine reasoning (e.g. in the form of machine learning and belief functions) on the one hand and methods and techniques for argumentation to aid human reasoning (e.g. for various forms of decision making and deliberation and for the Web) on the other. We also identify a number of open challenges if this potential is to be realised, and in particular the need for benchmark libraries.
Jezic G, Ossowski S, Toni F, et al., 2013, Preface to the special issue on Agreement Technologies, ARTIFICIAL INTELLIGENCE REVIEW, Vol: 39, Pages: 1-3, ISSN: 0269-2821
Schulz C, Toni F, 2013, ABA-Based Answer Set Justification., Theory Pract. Log. Program., Vol: 13
Fan X, Craven R, Singer R, et al., 2013, Assumption-Based Argumentation for Decision-Making with Preferences: A Medical Case Study, Publisher: SPRINGER-VERLAG BERLIN
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- Citations: 14
Baroni P, Romano M, Toni F, et al., 2013, An Argumentation-Based Approach for Automatic Evaluation of Design Debates, Publisher: SPRINGER-VERLAG BERLIN
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- Citations: 13
, 2013, Computational Logic in Multi-Agent Systems, Departmental Report, Publisher: Springer Berlin Heidelberg
Cabanillas D, Bonada F, Ventura R, et al., 2013, A combination of knowledge and argumentation based system for supporting injection mould design, 16th International Conference of the Catalan-Association-of-Artificial-Intelligence (CCIA), Publisher: IOS PRESS, Pages: 293-296, ISSN: 0922-6389
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- Citations: 2
Toni F, 2012, A generalised framework for dispute derivations in assumption-based argumentation, Artificial Intelligence, ISSN: 0004-3702
Modgil S, Toni F, 2012, Special Issue on Argumentation in Agreement Technologies, JOURNAL OF LOGIC AND COMPUTATION, Vol: 22, Pages: 953-956, ISSN: 0955-792X
Toni F, 2012, Reasoning on the web with assumption-based argumentation, Pages: 370-386, ISBN: 9783642331572
This tutorial provides an overview of computational argumentation, focusing on abstract argumentation and assumption-based argumentation, how they relate, as well as possible uses of the latter in Web contexts, and in particular the Semantic Web and Social Networks. The tutorial outlines achievements to date as well as (some) open issues. © 2012 Springer-Verlag.
Fan X, Toni F, 2012, Agent Strategies for ABA-based Information-seeking and Inquiry Dialogues, 20th European Conference on Artificial Intelligence (ECAI 2012), Publisher: IOS Press, Pages: 324-329
Mancarella P, Toni F, 2012, Semi-negative abductive logic programs with implicative integrity constraints: Semantics and properties, Pages: 33-51, ISBN: 9783642294136
We propose a novel semantics for semi-negative abductive logic programs (i.e. where the only negative literals are abducibles) with implicative integrity constraints (i.e. in the form of implications). This semantics combines answer set programming (with the implicative integrity constraints) and argumentation (for relevant explanations with the logic program, supported by abducibles). We argue that this semantics is better suited than the standard semantics to deal with applications of abductive logic programming and prove some properties of this semantics. We motivate our approach in an agent-based access control policy scenario. © 2012 Springer-Verlag Berlin Heidelberg.
Toni F, Torroni P, 2012, Bottom-up argumentation
Online social platforms, e-commerce sites and technical fora support the unfolding of informal exchanges, e.g. debates or discussions, that may be topic-driven or serendipitous. We outline a methodology for analysing these exchanges in computational argumentation terms, thus allowing a formal assessment of the dialectical validity of the positions debated in or emerging from the exchanges. Our methodology allows users to be engaged in this formal analysis and the assessment, within a dynamic process where comments, opinions, objections, as well as links connecting them, can all be contributed by users. © 2012 Springer-Verlag.
Fan X, Toni F, 2012, A first step towards argumentation dialogues for discovery
We present a formal model for two-agent discovery dialogues. The model allows agents to collectively discover a realization for a shared goal, using argumentation dialogues to exchange information. This information is in the form of rules, assumptions, and contraries of assumptions as in Assumption-based Argumentation (ABA). With dialogues, agents jointly build arguments and construct shared ABA frameworks. We define successful discovery dialogues as those giving admissible arguments that realize the shared goal. The main novelty of this paper is the modelling of the buttom-up relation between utterances. This new relation helps building "higher level" arguments from existing "lower level" supports, which we deem essential for discovery. © 2012 Springer-Verlag.
Modgil S, Oren N, Toni F, 2012, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface
Evripidou V, Toni F, 2012, Argumentation and voting for an intelligent user empowering business directory on the web, Pages: 209-212, ISSN: 0302-9743
We describe a new argumentation method for analysing opinion exchanges between on-line users aiding them to draw informative, structured and meaningful information. Our method combines different factors, such as social support drawn from votes and attacking/supporting relations between opinions interpreted as abstract arguments. We show a prototype web application which puts into use this method to offer an intelligent business directory allowing users to engage in debate and aid them to extract the dominant, emerging public opinion.
Craven R, Toni F, Cadar C, et al., 2012, Efficient argumentation for medical decision-making, Pages: 598-602, ISSN: 2334-1025
We describe the application of assumption-based argumentation (ABA) to a domain of medical knowledge derived from clinical trials of drugs for breast cancer. We adapt an algorithm for calculating the admissible semantics for ABA frameworks to take account of preferences and describe a prototype implementation which uses variant-based parallel computation to improve the efficiency of query answering. Copyright © 2012, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
Gao Y, Toni F, Craven R, 2012, Argumentation-Based Reinforcement Learning for RoboCup Soccer Keepaway, ECAI 2012, Publisher: IOS Press, Pages: 342-347, ISSN: 0922-6389
, 2012, Theorie and Applications of Formal Argumentation - First International Workshop, TAFA 2011. Barcelona, Spain, July 16-17, 2011, Revised Selected Papers, Publisher: Springer
Gao Y, Toni F, 2012, Argumentation Based Reinforcement Learning for RoboCup Soccer Keepaway, European Conference on Artificial Intelligence
Reinforcement Learning (RL) suffers from several difficulties when applied to domains with no obvious goal-state defined; this leads to inefficiency in RL algorithms. In this paper we consider a solution within the context of a widely-used testbed for RL, that of RoboCup Keepaway soccer. We introduce Argumentation-BasedRL (ABRL), using methods from argumentation theory to integrate domain knowledge, represented by arguments, into the SMDP algorithm for RL by using potential-based reward shaping. Empiricalresults show that ABRL outperforms the original SMDP algorithm, for this game, by improving the optimal performance.
, 2012, Proceedings of the First International Conference on Agreement Technologies, AT 2012, Dubrovnik, Croatia, October 15-16, 2012, Publisher: CEUR-WS.org
Fan X, Toni F, 2012, Argumentation Dialogues for Two-Agent Conflict Resolution, 4th Conference on Computational Models of Argument (COMMA), Publisher: IOS PRESS, Pages: 249-260, ISSN: 0922-6389
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- Citations: 2
Gao Y, Toni F, Craven R, 2012, Argumentation-Based Reinforcement Learning for RoboCup Keepaway, 4th Conference on Computational Models of Argument (COMMA), Publisher: IOS PRESS, Pages: 519-+, ISSN: 0922-6389
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- Citations: 2
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