256 research outputs found
Designing Normative Theories for Ethical and Legal Reasoning: LogiKEy Framework, Methodology, and Tool Support
A framework and methodology---termed LogiKEy---for the design and engineering
of ethical reasoners, normative theories and deontic logics is presented. The
overall motivation is the development of suitable means for the control and
governance of intelligent autonomous systems. LogiKEy's unifying formal
framework is based on semantical embeddings of deontic logics, logic
combinations and ethico-legal domain theories in expressive classic
higher-order logic (HOL). This meta-logical approach enables the provision of
powerful tool support in LogiKEy: off-the-shelf theorem provers and model
finders for HOL are assisting the LogiKEy designer of ethical intelligent
agents to flexibly experiment with underlying logics and their combinations,
with ethico-legal domain theories, and with concrete examples---all at the same
time. Continuous improvements of these off-the-shelf provers, without further
ado, leverage the reasoning performance in LogiKEy. Case studies, in which the
LogiKEy framework and methodology has been applied and tested, give evidence
that HOL's undecidability often does not hinder efficient experimentation.Comment: 50 pages; 10 figure
Automated reasoning in a collaborative problem solving process : A first approach
Collaborative systems are becoming a widely used tool particularly among professional communities and research groups. They provide a suitable context for distributed people working on the same subject to concentrate their work in a shared place to which everyone has access and can keep updated. The Semantic Web, intended to provide well defined semantics and cooperation between machines and people offers a range of technologies that underpin the development of intelligent collaborative systems. Defeasible reasoning has been shown to appropriately model common-sense reasoning. This work presents a first approach to incorporating defeasible reasoning with a software agent that collaborates with humans in a collaborative problem solving process. The process relies in a shared knowledge repository which is also modeled to incorporate defeasible knowledgeWorkshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI
Decision blocks: A tool for automating decision making in CLIPS
The human capability of making complex decision is one of the most fascinating facets of human intelligence, especially if vague, judgemental, default or uncertain knowledge is involved. Unfortunately, most existing rule based forward chaining languages are not very suitable to simulate this aspect of human intelligence, because of their lack of support for approximate reasoning techniques needed for this task, and due to the lack of specific constructs to facilitate the coding of frequently reoccurring decision block to provide better support for the design and implementation of rule based decision support systems. A language called BIRBAL, which is defined on the top of CLIPS, for the specification of decision blocks, is introduced. Empirical experiments involving the comparison of the length of CLIPS program with the corresponding BIRBAL program for three different applications are surveyed. The results of these experiments suggest that for decision making intensive applications, a CLIPS program tends to be about three times longer than the corresponding BIRBAL program
ArgFrame: A Multi-Layer, Web, Argument-Based Framework for Quantitative Reasoning
Multiple systems have been proposed to perform computational argumentation activities, but there is a lack of options for dealing with quantitative inferences. This multi-layer, web, argument-based framework has been proposed as a tool to perform automated reasoning with numerical data. It is able to use boolean logic for the creation of if-then rules and attacking rules. In turn, these rules/arguments can be activated or not by some input data, have their attacks solved (following some Dung or rank-based semantics), and finally aggregated in different fashions in order to produce a prediction (a number). The framework is implemented in PHP for the back-end. A JavaScript interface is provided for creating arguments, attacks among arguments, and performing case-by-case analyses
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