This paper aims to expose and analyze the potential foundational role of Argumentation for Human-... more This paper aims to expose and analyze the potential foundational role of Argumentation for Human-Centric AI, and to present the main challenges for this foundational role to be realized in a way that will fit well with the wider requirements and challenges of Human-Centric AI. The central idea set forward is that by endowing machines with the ability to argue with forms of machine argumentation that are cognitively compatible with those of human argumentation, we will be able to support a naturally effective, enhancing and ethical human-machine cooperation and “social” integration.
This paper develops a Reasoning about Actions and Change framework integrated with Default Reason... more This paper develops a Reasoning about Actions and Change framework integrated with Default Reasoning, suitable as a Knowledge Representation and Reasoning framework for Story Comprehension. The proposed framework, which is guided strongly by existing knowhow from the Psychology of Reading and Comprehension, is based on the theory of argumentation from AI. It uses argumentation to capture appropriate solutions to the frame, ramification and qualification problems and generalizations of these problems required for text comprehension. In this first part of the study the work concentrates on the central problem of integration (or elaboration) of the explicit information from the narrative in the text with the implicit (in the reader's mind) common sense world knowledge pertaining to the topic(s) of the story given in the text. We also report on our empirical efforts to gather background common sense world knowledge used by humans when reading a story and to evaluate, through a prototype system, the ability of our approach to capture both the majority and the variability of understanding of a story by the human readers in the experiments.
Developing systems that are aware of, and accommodate for, the cognitive capabilities and limitat... more Developing systems that are aware of, and accommodate for, the cognitive capabilities and limitations of human users is emerging as a key characteristic of a new paradigm of cognitive computing in Artificial Intelligence. According to this paradigm, the behavior of such cognitive systems is modeled on the behavior of human personal assistants, able to understand the motivations and personal likings / affinities of their interlocutors, while also being able to explain, and ultimately persuade the latter about, their computed solution (e.g., a proposed action) to a problem. This paper examines the link between argument and cognition from the psychological and the computational perspectives, and investigates how the synthesis of work on reasoning and narrative text comprehension from Cognitive Psychology and of work on computational argumentation from AI can offer a scientifically sound and pragmatic basis for building human-aware cognitive systems for everyday tasks. The paper aims, t...
We study how using argumentation as an alternative foundation for logic gives a framework in whic... more We study how using argumentation as an alternative foundation for logic gives a framework in which we can reconcile human and automated reasoning. We analyse this reconciliation between human and automated reasoning at three levels: (1) at the level of classical, strict reasoning on which, till today, automated reasoning and computing are based, (2) at the level of natural or ordinary human level reasoning as studied in cognitive psychology and which artificial intelligence, albeit in its early stages, is endeavouring to automate, and (3) at the level of the recently emerged cognitive computing paradigm where systems are required to be cognitively compatible with human reasoning based on common sense or expert knowledge, machine-learned from unstructured data in corpora over the web or other sources.
Argumentation has played a significant role in understanding and unifying under a common framewor... more Argumentation has played a significant role in understanding and unifying under a common framework di↵erent forms of defeasible reasoning in AI. Argumentation is also close to the original inception of logic as a framework for formalizing human 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 of Propositional Logic) and link this to support defeasible, Non-Monotonic Reasoning in AI. To this e↵ect, we propose Argumentation Logic and show properties and extensions thereof.
This paper presents a novel approach to modelling embedded agent dialogues. It proposes a specifi... more This paper presents a novel approach to modelling embedded agent dialogues. It proposes a specific structure for the supporting information accompanying the arguments that agents exchange during a dialogue, it defines formally how this information relates to the agent theory, and assigns to it semantics that is associated to each of the atomic dialogue types of the Walton-Krabbe typology. This allows the formal definition of necessary and sufficient initiation and acceptance conditions of licit dialectical shifts that are necessary for the modelling of embedded agent dialogues.
Information Integration is a young and exciting field with enormous research and commercial signi... more Information Integration is a young and exciting field with enormous research and commercial significance in the new world of the Information Society. It stands at the crossroad of Databases and Artificial Intelligence requiring novel techniques that bring together different methods ...
It is argued that in applications of concept learning from examples where not every possible cate... more It is argued that in applications of concept learning from examples where not every possible category of the domain is present in the training set (i.e., many real world applications), classification performance can be improved by integrating suitable discriminative and characteristic models of classification. The suggested approach is to first discriminate between the categories present in the training set and then characterize each of these categories against all possible categories. To show the viability of this approach, a number of different discriminators and characterizers are integrated and tested. In particular, a novel characterization method that makes use of the information about the statistical distribution of feature values that can be extracted from the training examples is used. By using this method it is possible to control the degree of generalization and to deal with dependencies among features.
Gorgias-B is a new tool that supports a methodology for the development of real life applications... more Gorgias-B is a new tool that supports a methodology for the development of real life applications. It can be used by nonargumentation experts generating and testing automatically the target argumentation theory in Gorgias.
Gorgias Cloud offers argumentation-based decision making as a service. The service includes an in... more Gorgias Cloud offers argumentation-based decision making as a service. The service includes an integrated development environment for the theories, testing and execution based on user scenarios, and, finally, an API for use by user applications. Gorgias is a structured argumentation framework where arguments are constructed using a basic scheme of argument rules. Two types of arguments are constructed within a Gorgias argumentation theory: object-level arguments and priority arguments expressing a preference between other arguments. Admissible composite arguments supporting a claim typically include both types of arguments. The Gorgias framework was introduced in [1], extended in [2] and applied to a variety of real-life application problems in [3]. The Gorgias system allows us to code argumentation theories of the form described above and subsequently query the system to find out if there is an admissible (composite) argument that supports a desired Claim. The system of Gorgias has been publicly available since 2003 and has been used by several research groups to develop prototype real-life applications of argumentation in a variety of application domains. Today, it is available as a service over the internet with Gorgias Cloud, which provides an integrated environment for developing applications of argumentation with three novel features:
The area of argumentation is now at a stage that it can benefit from the study of systematic meth... more The area of argumentation is now at a stage that it can benefit from the study of systematic methodologies for building applications of argumentation. Herein, we present such a systematic argumentation software methodology, called SoDA (Software Development for Argumentation), that facilitates the principled modeling of real life problems, and the Gorgias-B tool that supports it. Gorgias-B builds on the system Gorgias that implements the theoretical framework proposed in [1]. SoDA and Gorgias-B built on the successful use of Gorgias during the last ten years by different users for developing real life applications (see http://gorgiasb.tuc.gr/Apps.html).
Handbook of Logic in Artificial Intelligence and Logic Programming: Volume 5: Logic Programming, 1998
This paper extends and updates our earlier survey and analysis of work on the extension of logic ... more This paper extends and updates our earlier survey and analysis of work on the extension of logic programming to perform abductive reasoning [Kakas et al., 1993]. The purpose of the paper is to provide a critical overview of some of the main research results, in order to develop a common framework for evaluating these results, to identify the main unresolved problems, and to indicate directions for future work. The emphasis is not on technical details but on relationships and common features of different approaches. Some of the main issues we will consider are the contributions that abduction can make to the problems of reasoning with incomplete or negative information, the evolution of knowledge, and the semantics of logic programming and its extensions. We also discuss recent work on the argumentation-theoretic interpretation of abduction, which was introduced in the earlier version of this paper. The philosopher Peirce first introduced the notion of abduction. In [Peirce, 1931-58]...
This paper presents the past and present efforts of developing real-life applications of argument... more This paper presents the past and present efforts of developing real-life applications of argumentation with the Gorgias preference-based structured argumentation framework of Logic Programming with Priorities. Since its free availability on the web in 2003, the Gorgias system has been used by different groups in a variety of real-life applications in areas such as medical support, network security, business computing, ambient intelligence and, recently, in the area of cognitive personal assistants. We briefly review the Gorgias framework and its past applications and present an emerging general methodological approach for developing "decision making" applications of argumentation. This approach allows the development of real world applications directly from their high-level requirements expressed in the language of the application without the need for familiarity with the underlying technical details of argumentation. A new tool, called Gorgias-B, supports this high-level development of applications and automatically generates the underlying argumentation theory in Gorgias code. The paper also reports on ongoing real-life applications in two domains: an eye-clinic assistant for first level support, and systems for patient data access and data sharing agreements according to the relevant legislation and contracts or policies of the several stakeholders involved. The proposed approach is quite general for this type of applications of argumentation and, thus, it can be used with any preference-based argumentation framework.
This paper studies the application of argumentation theory and methods from Artificial Intelligen... more This paper studies the application of argumentation theory and methods from Artificial Intelligence to the problem of conflict resolution. It shows how the decision theories of each of the parties involved in a conflict can be captured and formalized within a framework of preference-based argumentation. In particular, it studies how the SoDA methodology and its support tool, Gorgias-B for developing argumentation software, facilitate the elucidation of each party’s preferences over their available options for addressing the conflict, and, through this, the construction of appropriate argumentation theories corresponding to the decision theories of the parties involved. These argumentation theories are generated automatically and can be executed directly to find out the position of each party at any particular stage of the negotiation process. This connection between argumentation and conflict resolution is illustrated through a real-life example of conflict resolution between the US and China after a plane collision.
We describe a system implementing a novel extension of Fung and Kowalski's IFF abductive proof pr... more We describe a system implementing a novel extension of Fung and Kowalski's IFF abductive proof procedure which we call CIFF, and its application to realise intelligent agents that can construct (partial or complete) plans and react to changes in the environment. CIFF extends the original IFF procedure in two ways: by dealing with constraint predicates and by dealing with non-allowed abductive logic programs.
We describe an application of Abductive Logic Programming (ALP) to the analysis of an important c... more We describe an application of Abductive Logic Programming (ALP) to the analysis of an important class of DNA microarray experiments. These experiments measure differences in expression levels of whole genomes in differing environmental conditions and/or after deletion or overexpression of one or more genes. Their aim is to obtain insights about gene interactions and gene pathways. We develop an ALP theory that provides a simple and general model of how gene interactions can cause changes in observable expression levels of genes. Input to the procedure are the observed microarray results; output are hypotheses about possible gene interactions that explain the observed effects. A key feature of the model are parameters that encode different biological assumptions and provide a means of constraining the search for possible hypotheses. We have applied and evaluated our approach on microarray experiments on M.tuberculosis and on S.cerevisiae (yeast). Comparison of inferred hypotheses against known gene regulation networks and known gene functions in the biological literature provide a form of independent validation of the model.
This paper aims to expose and analyze the potential foundational role of Argumentation for Human-... more This paper aims to expose and analyze the potential foundational role of Argumentation for Human-Centric AI, and to present the main challenges for this foundational role to be realized in a way that will fit well with the wider requirements and challenges of Human-Centric AI. The central idea set forward is that by endowing machines with the ability to argue with forms of machine argumentation that are cognitively compatible with those of human argumentation, we will be able to support a naturally effective, enhancing and ethical human-machine cooperation and “social” integration.
This paper develops a Reasoning about Actions and Change framework integrated with Default Reason... more This paper develops a Reasoning about Actions and Change framework integrated with Default Reasoning, suitable as a Knowledge Representation and Reasoning framework for Story Comprehension. The proposed framework, which is guided strongly by existing knowhow from the Psychology of Reading and Comprehension, is based on the theory of argumentation from AI. It uses argumentation to capture appropriate solutions to the frame, ramification and qualification problems and generalizations of these problems required for text comprehension. In this first part of the study the work concentrates on the central problem of integration (or elaboration) of the explicit information from the narrative in the text with the implicit (in the reader's mind) common sense world knowledge pertaining to the topic(s) of the story given in the text. We also report on our empirical efforts to gather background common sense world knowledge used by humans when reading a story and to evaluate, through a prototype system, the ability of our approach to capture both the majority and the variability of understanding of a story by the human readers in the experiments.
Developing systems that are aware of, and accommodate for, the cognitive capabilities and limitat... more Developing systems that are aware of, and accommodate for, the cognitive capabilities and limitations of human users is emerging as a key characteristic of a new paradigm of cognitive computing in Artificial Intelligence. According to this paradigm, the behavior of such cognitive systems is modeled on the behavior of human personal assistants, able to understand the motivations and personal likings / affinities of their interlocutors, while also being able to explain, and ultimately persuade the latter about, their computed solution (e.g., a proposed action) to a problem. This paper examines the link between argument and cognition from the psychological and the computational perspectives, and investigates how the synthesis of work on reasoning and narrative text comprehension from Cognitive Psychology and of work on computational argumentation from AI can offer a scientifically sound and pragmatic basis for building human-aware cognitive systems for everyday tasks. The paper aims, t...
We study how using argumentation as an alternative foundation for logic gives a framework in whic... more We study how using argumentation as an alternative foundation for logic gives a framework in which we can reconcile human and automated reasoning. We analyse this reconciliation between human and automated reasoning at three levels: (1) at the level of classical, strict reasoning on which, till today, automated reasoning and computing are based, (2) at the level of natural or ordinary human level reasoning as studied in cognitive psychology and which artificial intelligence, albeit in its early stages, is endeavouring to automate, and (3) at the level of the recently emerged cognitive computing paradigm where systems are required to be cognitively compatible with human reasoning based on common sense or expert knowledge, machine-learned from unstructured data in corpora over the web or other sources.
Argumentation has played a significant role in understanding and unifying under a common framewor... more Argumentation has played a significant role in understanding and unifying under a common framework di↵erent forms of defeasible reasoning in AI. Argumentation is also close to the original inception of logic as a framework for formalizing human 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 of Propositional Logic) and link this to support defeasible, Non-Monotonic Reasoning in AI. To this e↵ect, we propose Argumentation Logic and show properties and extensions thereof.
This paper presents a novel approach to modelling embedded agent dialogues. It proposes a specifi... more This paper presents a novel approach to modelling embedded agent dialogues. It proposes a specific structure for the supporting information accompanying the arguments that agents exchange during a dialogue, it defines formally how this information relates to the agent theory, and assigns to it semantics that is associated to each of the atomic dialogue types of the Walton-Krabbe typology. This allows the formal definition of necessary and sufficient initiation and acceptance conditions of licit dialectical shifts that are necessary for the modelling of embedded agent dialogues.
Information Integration is a young and exciting field with enormous research and commercial signi... more Information Integration is a young and exciting field with enormous research and commercial significance in the new world of the Information Society. It stands at the crossroad of Databases and Artificial Intelligence requiring novel techniques that bring together different methods ...
It is argued that in applications of concept learning from examples where not every possible cate... more It is argued that in applications of concept learning from examples where not every possible category of the domain is present in the training set (i.e., many real world applications), classification performance can be improved by integrating suitable discriminative and characteristic models of classification. The suggested approach is to first discriminate between the categories present in the training set and then characterize each of these categories against all possible categories. To show the viability of this approach, a number of different discriminators and characterizers are integrated and tested. In particular, a novel characterization method that makes use of the information about the statistical distribution of feature values that can be extracted from the training examples is used. By using this method it is possible to control the degree of generalization and to deal with dependencies among features.
Gorgias-B is a new tool that supports a methodology for the development of real life applications... more Gorgias-B is a new tool that supports a methodology for the development of real life applications. It can be used by nonargumentation experts generating and testing automatically the target argumentation theory in Gorgias.
Gorgias Cloud offers argumentation-based decision making as a service. The service includes an in... more Gorgias Cloud offers argumentation-based decision making as a service. The service includes an integrated development environment for the theories, testing and execution based on user scenarios, and, finally, an API for use by user applications. Gorgias is a structured argumentation framework where arguments are constructed using a basic scheme of argument rules. Two types of arguments are constructed within a Gorgias argumentation theory: object-level arguments and priority arguments expressing a preference between other arguments. Admissible composite arguments supporting a claim typically include both types of arguments. The Gorgias framework was introduced in [1], extended in [2] and applied to a variety of real-life application problems in [3]. The Gorgias system allows us to code argumentation theories of the form described above and subsequently query the system to find out if there is an admissible (composite) argument that supports a desired Claim. The system of Gorgias has been publicly available since 2003 and has been used by several research groups to develop prototype real-life applications of argumentation in a variety of application domains. Today, it is available as a service over the internet with Gorgias Cloud, which provides an integrated environment for developing applications of argumentation with three novel features:
The area of argumentation is now at a stage that it can benefit from the study of systematic meth... more The area of argumentation is now at a stage that it can benefit from the study of systematic methodologies for building applications of argumentation. Herein, we present such a systematic argumentation software methodology, called SoDA (Software Development for Argumentation), that facilitates the principled modeling of real life problems, and the Gorgias-B tool that supports it. Gorgias-B builds on the system Gorgias that implements the theoretical framework proposed in [1]. SoDA and Gorgias-B built on the successful use of Gorgias during the last ten years by different users for developing real life applications (see http://gorgiasb.tuc.gr/Apps.html).
Handbook of Logic in Artificial Intelligence and Logic Programming: Volume 5: Logic Programming, 1998
This paper extends and updates our earlier survey and analysis of work on the extension of logic ... more This paper extends and updates our earlier survey and analysis of work on the extension of logic programming to perform abductive reasoning [Kakas et al., 1993]. The purpose of the paper is to provide a critical overview of some of the main research results, in order to develop a common framework for evaluating these results, to identify the main unresolved problems, and to indicate directions for future work. The emphasis is not on technical details but on relationships and common features of different approaches. Some of the main issues we will consider are the contributions that abduction can make to the problems of reasoning with incomplete or negative information, the evolution of knowledge, and the semantics of logic programming and its extensions. We also discuss recent work on the argumentation-theoretic interpretation of abduction, which was introduced in the earlier version of this paper. The philosopher Peirce first introduced the notion of abduction. In [Peirce, 1931-58]...
This paper presents the past and present efforts of developing real-life applications of argument... more This paper presents the past and present efforts of developing real-life applications of argumentation with the Gorgias preference-based structured argumentation framework of Logic Programming with Priorities. Since its free availability on the web in 2003, the Gorgias system has been used by different groups in a variety of real-life applications in areas such as medical support, network security, business computing, ambient intelligence and, recently, in the area of cognitive personal assistants. We briefly review the Gorgias framework and its past applications and present an emerging general methodological approach for developing "decision making" applications of argumentation. This approach allows the development of real world applications directly from their high-level requirements expressed in the language of the application without the need for familiarity with the underlying technical details of argumentation. A new tool, called Gorgias-B, supports this high-level development of applications and automatically generates the underlying argumentation theory in Gorgias code. The paper also reports on ongoing real-life applications in two domains: an eye-clinic assistant for first level support, and systems for patient data access and data sharing agreements according to the relevant legislation and contracts or policies of the several stakeholders involved. The proposed approach is quite general for this type of applications of argumentation and, thus, it can be used with any preference-based argumentation framework.
This paper studies the application of argumentation theory and methods from Artificial Intelligen... more This paper studies the application of argumentation theory and methods from Artificial Intelligence to the problem of conflict resolution. It shows how the decision theories of each of the parties involved in a conflict can be captured and formalized within a framework of preference-based argumentation. In particular, it studies how the SoDA methodology and its support tool, Gorgias-B for developing argumentation software, facilitate the elucidation of each party’s preferences over their available options for addressing the conflict, and, through this, the construction of appropriate argumentation theories corresponding to the decision theories of the parties involved. These argumentation theories are generated automatically and can be executed directly to find out the position of each party at any particular stage of the negotiation process. This connection between argumentation and conflict resolution is illustrated through a real-life example of conflict resolution between the US and China after a plane collision.
We describe a system implementing a novel extension of Fung and Kowalski's IFF abductive proof pr... more We describe a system implementing a novel extension of Fung and Kowalski's IFF abductive proof procedure which we call CIFF, and its application to realise intelligent agents that can construct (partial or complete) plans and react to changes in the environment. CIFF extends the original IFF procedure in two ways: by dealing with constraint predicates and by dealing with non-allowed abductive logic programs.
We describe an application of Abductive Logic Programming (ALP) to the analysis of an important c... more We describe an application of Abductive Logic Programming (ALP) to the analysis of an important class of DNA microarray experiments. These experiments measure differences in expression levels of whole genomes in differing environmental conditions and/or after deletion or overexpression of one or more genes. Their aim is to obtain insights about gene interactions and gene pathways. We develop an ALP theory that provides a simple and general model of how gene interactions can cause changes in observable expression levels of genes. Input to the procedure are the observed microarray results; output are hypotheses about possible gene interactions that explain the observed effects. A key feature of the model are parameters that encode different biological assumptions and provide a means of constraining the search for possible hypotheses. We have applied and evaluated our approach on microarray experiments on M.tuberculosis and on S.cerevisiae (yeast). Comparison of inferred hypotheses against known gene regulation networks and known gene functions in the biological literature provide a form of independent validation of the model.
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Papers by Antonis Kakas