This paper formally compares some central notions from two well-known formalisms for rule-based argumentation, DeLP and ASPIC+. The comparisons especially focus on intuitive adequacy and inter-translatability, consistency, and closure properties. As for differences in the definitions of arguments and attack, it turns out that DeLP's definitions are intuitively appealing but that they may not fully comply with Caminada and Amgoud's rationality postulates of strict closure and indirect consistency. For some special cases, the DeLP definitions are shown to fare better than ASPIC+. Next, it is argued that there are reasons to consider a variant of DeLP with grounded semantics, since in some examples its current notion of warrant arguably has counterintuitive consequences and may lead to sets of warranted arguments that are not admissible. Finally, under some minimality and consistency assumptions on ASPIC+ arguments, a one-to-many correspondence between ASPIC+ arguments and DeLP arguments is identified in such a way that if the DeLP warranting procedure is changed to grounded semantics, then DeLP notion of warrant and ASPIC+'s notion of justification are equivalent. This result is proven for three alternative definitions of attack.

This paper builds on the recent ASPIC+ formalism, to develop a general framework for argumentation with preferences. We motivate a revised definition of conflict free sets of arguments, adapt ASPIC+ to accommodate a broader range of instantiating logics, and show that under some assumptions, the resulting framework satisfies key properties and rationality postulates. We then show that the generalised framework accommodates Tarskian logic instantiations extended with preferences, and then study instantiations of the framework by classical logic approaches to argumentation. We conclude by arguing that ASPIC+'s modelling of defeasible inference rules further testifies to the generality of the framework, and then examine and counter recent critiques of Dung's framework and its extensions to accommodate preferences.

Towards Artificial Argumentation

The field of computational models of argument is emerging as an important aspect of artificial intelligence research. The reason for this is based on the recognition that if we are to develop robust intelligent systems, then it is imperative that they can handle incomplete and inconsistent information in a way that somehow emulates the way humans tackle such a complex task. And one of the key ways that humans do this is to use argumentation either internally, by evaluating arguments and counterarguments‚ or externally, by for instance entering into a discussion or debate where arguments are exchanged. As we report in this review, recent developments in the field are leading to technology for artificial argumentation, in the legal, medical, and e-government domains, and interesting tools for argument mining, for debating technologies, and for argumentation solvers are emerging.

Carneades is a recently proposed formalism for structured argumentation with varying proof standards. An open question is its relation with Dung's seminal abstract approach to argumentation. In this paper the two formalisms are formally related by translating Carneades into ASPIC+, another recently proposed formalism for structured argumentation. Since ASPIC+ is defined to generate Dung-style abstract argumentation frameworks, this in effect translates Carneades graphs into abstract argumentation frameworks. It is proven that Carneades always induces a unique Dung extension, which is the same in all of Dung's semantics.

The Association for the Advancement of Artificial Intelligence was pleased to present the 2009 Fall Symposium Series, held Thursday through Saturday, November 5–7, at the Westin Arlington Gateway in Arlington, Virginia. The Symposium Series was preceded on Wednesday, November 4 by a one-day AI funding seminar. The titles of the seven symposia were as follows: (1) Biologically Inspired Cognitive Architectures, (2) Cognitive and Metacognitive Educational Systems, (3) Complex Adaptive Systems and the Threshold Effect: Views from the Natural and Social Sciences, (4) Manifold Learning and Its Applications, (5) Multirepresentational Architectures for Human-Level Intelligence, (6) The Uses of Computational Argumentation, and (7) Virtual Healthcare Interaction.

Series, held Thursday through Saturday, November 5-7, at he Association for the Advancement of Artificial Intelligence the Westin Arlington Gateway in Arlington, Virginia. The titles of the seven symposia were as follows: (1) Biologically Inspired Cognitive Biologically Inspired Cognitive Architectures Architectures, (2) Cognitive and Metacognitive Cognitive and Metacognitive Educational Systems Educational Systems, (3) Complex Adaptive Complex Adaptive Systems and the Threshold Effect: Views from the Natural Systems and the Threshold Effect: Views and Social Sciences from the Natural and Social Sciences, (4) Manifold Manifold Learning and Its Applications Learning and Its Applications, (5) Multirepresentational Architectures for Human-Level Multirepresentational Architectures for Human-Level Intelligence Intelligence, (6) The Uses of Computational The Uses of Computational Argumentation Argumentation, and (7) Virtual Healthcare Virtual Healthcare Interaction Interaction. An informal reception was held on Thursday, November 5. A general plenary session, in which the highlights of each symposium were presented, was held on Friday, November 6. The challenge of creating a real-life computational equivalent of the human mind requires that we better understand at a computational level how natural intelligent systems develop their cognitive and learning functions. They will behave, variety of disjoined communities and schools of learn, communicate, and "think" as conscious thought that used to speak different languages and beings in general, in addition to being able to perform ignore each other.

Argumentation is a form of reasoning that makes explicit the reasons for the conclusions that are drawn and how con- flicts between reasons are resolved. This provides a natural mechanism, for example, to handle inconsistent and uncer- tain information and to resolve conflicts of opinion between intelligent agents. The advantage of a mechanism based on argumentation is that considering the reasons behind the conclusions offers more than considering the conclusions alone (to adapt something Isaac Bashevis Singer once said, the approach has “more vitamins” than other approaches to reasoning). For example, in dealing with inconsistent infor- mation, an early use of argumentation, it is possible to know more than just that we have the inconsistent conclusions p and not p. We can establish exactly which pieces of infor- mation lead to these conclusions and can then prioritize one conclusion over another on the basis of this information, de- cide what information should be revised to achieve consis- tency, or even determine what additional investigation needs to be carried out (when we have reason to believe both that it is raining outside and not raining outside, and have no way of determining which is correct, going to look may be the best solution).