Normative Practical Reasoning via Argumentation and Dialogue

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Strong Admissibility Revisited

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Routinisation of Audience Participation: BBC News Online, Citizenship and Democratic Debate

Leading up to the 2010 UK general election, Director General of the BBC, Mark Thompson, stressed the importance of the Corporation’s ability ‘to provide a strong and independent space where the big debates can take place, free from political or commercial influence’. ‘In this public space,’ he continued, ‘everyone can have access to the lifeblood of healthy democratic debate – impartial news and information’. Affirming the importance of BBC Online, Thompson described it as ‘being a cornerstone of what the BBC should be about’ (Thompson, 2010). As with previous elections, one of the key strategic priorities for the BBC’s Election 2010 website was to help inform the citizenry about the campaign and empower voters to make an informed choice. In the most traditional sense, this was achieved through the BBC’s journalism and a series of rich background features – e.g. guidance on voting procedures, MPs and parliamentary politics, and comparisons of party manifestos. The BBC election websites have also featured experimentation with various forms of audience engagement, exemplified by different interactive features on the BBC micro websites for the 1997, 2001, 2005 and 2010 UK general elections. This has traditionally been anchored in the Corporation’s public service commitment to facilitating ‘civic engagement’ and providing ‘democratic value’ to British citizens (see also Thorsen et al., 2009, Thorsen, 2010, 2011, Allan and Thorsen, 2010). The BBC’s news website was incredibly popular during the 2010 election according to visitor statistics. On results day, May 7, BBC News Online had 11.4 million individual users, breaking the previous record set on November 5, 2008, for the election of Barack Obama as US President (Herrmann, 2010). Comparing this to 2005, the number of unique visitors to the BBC’s election site on results day, May 6, was 3 million taking the overall BBC News Online total to 4.3 million (Ward, 2006:17). This demonstrates a near three-fold increase in individual users from one election to the next and indicates that whilst the internet might not be perceived as having had a significant impact on the election outcomes, the BBC has certainly had a considerable impact on citizens’ online activities. Based on a larger study into BBC’s election websites involving interviews, observations and textual analysis, this chapter will examine how audience participation had by 2010 become a routinised part of the Corporation’s newsroom. It will begin by providing an historical overview of how public access programming has developed within the BBC and its influence on how the Corporation has sought to facilitate participatory spaces online. Following a discussion of online participatory spaces on the BBC’s election websites, it will offer a critique of how these are operationalized internally. It will argue that despite converged newsroom practices, the scale of the BBC’s operations means facilitation of civic engagement is fragmented between competing stakeholders within the Corporation each with their own routinised practices and perception of its value. This tension has a dramatic effect not only on the dialectic relationship between BBC journalists and its audiences, but also on the type of ‘public space’ the Corporation is able to foster and by extension the empowerment of citizens to engage in ‘healthy democratic debate’

Algorithms and Complexity Results for Persuasive Argumentation

The study of arguments as abstract entities and their interaction as introduced by Dung (Artificial Intelligence 177, 1995) has become one of the most active research branches within Artificial Intelligence and Reasoning. A main issue for abstract argumentation systems is the selection of acceptable sets of arguments. Value-based argumentation, as introduced by Bench-Capon (J. Logic Comput. 13, 2003), extends Dung's framework. It takes into account the relative strength of arguments with respect to some ranking representing an audience: an argument is subjectively accepted if it is accepted with respect to some audience, it is objectively accepted if it is accepted with respect to all audiences. Deciding whether an argument is subjectively or objectively accepted, respectively, are computationally intractable problems. In fact, the problems remain intractable under structural restrictions that render the main computational problems for non-value-based argumentation systems tractable. In this paper we identify nontrivial classes of value-based argumentation systems for which the acceptance problems are polynomial-time tractable. The classes are defined by means of structural restrictions in terms of the underlying graphical structure of the value-based system. Furthermore we show that the acceptance problems are intractable for two classes of value-based systems that where conjectured to be tractable by Dunne (Artificial Intelligence 171, 2007)

Asymmetry of the Kolmogorov complexity of online predicting odd and even bits

Symmetry of information states that $C(x) + C(y|x) = C(x,y) + O(\log C(x))$. We show that a similar relation for online Kolmogorov complexity does not hold. Let the even (online Kolmogorov) complexity of an n-bitstring $x_1x_2... x_n$ be the length of a shortest program that computes $x_2$ on input $x_1$, computes $x_4$ on input $x_1x_2x_3$, etc; and similar for odd complexity. We show that for all n there exist an n-bit x such that both odd and even complexity are almost as large as the Kolmogorov complexity of the whole string. Moreover, flipping odd and even bits to obtain a sequence $x_2x_1x_4x_3\ldots$, decreases the sum of odd and even complexity to $C(x)$.Comment: 20 pages, 7 figure

A Theory of Formal Synthesis via Inductive Learning

Formal synthesis is the process of generating a program satisfying a high-level formal specification. In recent times, effective formal synthesis methods have been proposed based on the use of inductive learning. We refer to this class of methods that learn programs from examples as formal inductive synthesis. In this paper, we present a theoretical framework for formal inductive synthesis. We discuss how formal inductive synthesis differs from traditional machine learning. We then describe oracle-guided inductive synthesis (OGIS), a framework that captures a family of synthesizers that operate by iteratively querying an oracle. An instance of OGIS that has had much practical impact is counterexample-guided inductive synthesis (CEGIS). We present a theoretical characterization of CEGIS for learning any program that computes a recursive language. In particular, we analyze the relative power of CEGIS variants where the types of counterexamples generated by the oracle varies. We also consider the impact of bounded versus unbounded memory available to the learning algorithm. In the special case where the universe of candidate programs is finite, we relate the speed of convergence to the notion of teaching dimension studied in machine learning theory. Altogether, the results of the paper take a first step towards a theoretical foundation for the emerging field of formal inductive synthesis