The formal-logical characterisation of lies, deception, and associated notions
Defining various dishonest notions in a formal way is a key step to enable intelligent agents to act in untrustworthy environments. This review evaluates the literature for this topic by looking at formal definitions based on modal logic as well as other formal approaches. Criteria from philosophical groundwork is used to assess the definitions for correctness and completeness. The key contribution of this review is to show that only a few definitions fully comply with this gold standard and to point out the missing steps towards a successful application of these definitions in an actual agent environment.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
A Multimodal Dataset for Deception Detection
This paper presents the construction of a multimodal dataset for deception detection, including physiological, thermal, and visual responses of human subjects under three deceptive scenarios. We present the experimental …
Deception DetectionFormulating Manipulable Argumentation with Intra-/Inter-Agent Preferences
From marketing to politics, exploitation of incomplete information through selective communication of arguments is ubiquitous. In this work, we focus on development of an argumentation-theoretic model for manipulable mul…
MarketingAI Deception: Risks, Dynamics, and Controls
As intelligence increases, so does its shadow. AI deception, in which systems induce false beliefs to secure self-beneficial outcomes, has evolved from a speculative concern to an empirically demonstrated risk across lan…
Probing the Limits of the Lie Detector Approach to LLM Deception
Mechanistic approaches to deception in large language models (LLMs) often rely on "lie detectors", that is, truth probes trained to identify internal representations of model outputs as false. The lie detector approach t…
DeceptionX: From Multimodal Evidence to Explainable Deception Detection
Deception detection is a critical and highly challenging task within affective computing and behavioral analysis. Existing deep learning methods typically treat this task as a straightforward classification problem; howe…
Logical Reasoning