676 research outputs found
A Duality-Aware Calculus for Quantified Boolean Formulas
Wir präsentieren ein formales Rahmenwerk, das es ermöglicht das Verhalten von QBF-Beweisen zu beschreiben.Learning and backjumping are essential features in search-based decision procedures for Quantified Boolean Formulas (QBF). To obtain a better understanding of such procedures, we present a formal framework, which allows to simultaneously reason on prenex conjunctive and disjunctive normal form. It captures both satisfying and falsifying search states in a symmetric way. This symmetry simplifies the framework and offers potential for further variants.W1255-N23S11408-N23(VLID)193237
Deontic Logic and Natural Language
There has been a recent surge of work on deontic modality within philosophy of language. This work has put the deontic logic tradition in contact with natural language semantics, resulting in significant increase in sophistication on both ends. This chapter surveys the main motivations, achievements, and prospects of this work
"If you'd wiggled A, then B would've changed":Causality and counterfactual conditionals
This paper deals with the truth conditions of conditional sentences. It focuses on a particular class of problematic examples for semantic theories for these sentences. I will argue that the examples show the need to refer to dynamic, in particular causal laws in an approach to their truth conditions. More particularly, I will claim that we need a causal notion of consequence. The proposal subsequently made uses a representation of causal dependencies as proposed in Pearl (2000) to formalize a causal notion of consequence. This notion inserted in premise semantics for counterfactuals in the style of Veltman (1976) and Kratzer (1979) will provide a new interpretation rule for conditionals. I will illustrate how this approach overcomes problems of previous proposals and end with some remarks on remaining questions
End user programming of awareness systems : addressing cognitive and social challenges for interaction with aware environments
The thesis is put forward that social intelligence in awareness systems emerges from end-Users themselves through the mechanisms that support them in the development and maintenance of such systems. For this intelligence to emerge three challenges have to be addressed, namely the challenge of appropriate awareness abstractions, the challenge of supportive interactive tools, and the challenge of infrastructure. The thesis argues that in order to advance towards social intelligent awareness systems, we should be able to interpret and predict the success or failure of such systems in relationship to their communicational objectives and their implications for the social interactions they support. The FN-AAR (Focus-Nimbus Aspects Attributes Resources) model is introduced as a formal model which by capturing the general characteristics of the awareness-systems domain allows predictions about socially salient patterns pertaining to human communication and brings clarity to the discussion around relevant concepts such as social translucency, symmetry, and deception. The thesis recognizes that harnessing the benefits of context awareness can be problematic for end-users and other affected individuals, who may not always be able to anticipate, understand or appreciate system function, and who may so feel their own sense of autonomy and privacy threatened. It introduces a set of tools and mechanisms that support end-user control, system intelligibility and accountability. This is achieved by minimizing the cognitive effort needed to handle the increased complexity of such systems and by enhancing the ability of people to configure and maintain intelligent environments. We show how these tools and mechanisms empower end-users to answer questions such as "how does the system behave", "why is something happening", "how would the system behave in response to a change in context", and "how can the system’s behaviour be altered" to achieve intelligibility, accountability, and end-user control. Finally, the thesis argues that awareness applications overall can not be examined as static configurations of services and functions, and that they should be seen as the results of both implicit and explicit interaction with the user. Amelie is introduced as a supportive framework for the development of context-aware applications that encourages the design of the interactive mechanisms through which end-users can control, direct and advance such systems dynamically throughout their deployment. Following the recombinant computing approach, Amelie addresses the implications of infrastructure design decisions on user experience, while by adopting the premises of the FN-AAR model Amelie supports the direct implementation of systems that allow end-users to meet social needs and to practice extant social skills
Moral Responsibility for AI Systems
As more and more decisions that have a significant ethical dimension are
being outsourced to AI systems, it is important to have a definition of moral
responsibility that can be applied to AI systems. Moral responsibility for an
outcome of an agent who performs some action is commonly taken to involve both
a causal condition and an epistemic condition: the action should cause the
outcome, and the agent should have been aware -- in some form or other -- of
the possible moral consequences of their action. This paper presents a formal
definition of both conditions within the framework of causal models. I compare
my approach to the existing approaches of Braham and van Hees (BvH) and of
Halpern and Kleiman-Weiner (HK). I then generalize my definition into a degree
of responsibility.Comment: Accepted at NeurIPS 202
- …