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Related papers: Arguing Ecosystem Values with Paraconsistent Logic…

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Environmental science almost invariably proposes problems of extreme complexity, typically characterized by strongly nonlinear evolution dynamics. The systems under investigation have many degrees of freedom - which makes them complicated -…

Atmospheric and Oceanic Physics · Physics 2007-05-23 A. Speranza , V. Lucarini

We introduce a new semantics for justification logic based on subset relations. Instead of using the established and more symbolic interpretation of justifications, we model justifications as sets of possible worlds. We introduce a new…

Logic · Mathematics 2020-08-19 Eveline Lehmann , Thomas Studer

This paper develops a declarative language, P-log, that combines logical and probabilistic arguments in its reasoning. Answer Set Prolog is used as the logical foundation, while causal Bayes nets serve as a probabilistic foundation. We give…

Artificial Intelligence · Computer Science 2008-12-04 Chitta Baral , Michael Gelfond , Nelson Rushton

Ontologies formalise how the concepts from a given domain are interrelated. Despite their clear potential as a backbone for explainable AI, existing ontologies tend to be highly incomplete, which acts as a significant barrier to their more…

Artificial Intelligence · Computer Science 2021-05-12 Steven Schockaert , Yazmín Ibáñez-García , Víctor Gutiérrez-Basulto

Predictive Process Analytics is becoming an essential aid for organizations, providing online operational support of their processes. However, process stakeholders need to be provided with an explanation of the reasons why a given process…

Information value, a measure for decision sensitivity, can provide essential information in engineering and environmental assessments. It quantifies the potential for improved decision-making when reducing uncertainty in specific inputs. By…

Multi-context systems provide a powerful framework for modelling information-aggregation systems featuring heterogeneous reasoning components. Their execution can, however, incur non-negligible cost. Here, we focus on cost-complexity of…

Artificial Intelligence · Computer Science 2014-05-29 Peter Novák , Cees Witteveen

A novel mathematical framework is proposed to describe the ecological and evolutionary consequences of consumer--resource interactions. Both the consumer and resource are assumed to consist of several (sub)species, which interact between…

Populations and Evolution · Quantitative Biology 2025-11-11 Alexander S. Bratus , Sergei V. Drozhzhin , Artem S. Novozhilov

This paper explores relational syllogistic logics, a family of logical systems related to reasoning about relations in extensions of the classical syllogistic. These are all decidable logical systems. We prove completeness theorems and…

Logic · Mathematics 2023-06-22 Alex Kruckman , Lawrence S. Moss

Economists model knowledge use and acquisition as a cause-and-effect calculus associating observations made by a decision-maker about their world with possible underlying causes. Knowledge models are well-established for static contexts,…

Neural and Evolutionary Computing · Computer Science 2024-12-03 Abigail Devereaux , Roger Koppl

We examined a four-valued logic method for state settings in conflict resolution models. Decision-making models of conflict resolution, such as game theory and graph model for conflict resolution (GMCR), assume the description of a state to…

Artificial Intelligence · Computer Science 2024-10-28 Yukiko Kato

Temporal logics over finite traces have recently seen wide application in a number of areas, from business process modelling, monitoring, and mining to planning and decision making. However, real-life dynamic systems contain a degree of…

Logic in Computer Science · Computer Science 2019-11-19 Fabrizio M. Maggi , Marco Montali , Rafael Peñaloza

We describe cases where real recommender systems were modified in the service of various human values such as diversity, fairness, well-being, time well spent, and factual accuracy. From this we identify the current practice of values…

Information Retrieval · Computer Science 2021-07-26 Jonathan Stray , Ivan Vendrov , Jeremy Nixon , Steven Adler , Dylan Hadfield-Menell

Market-based mechanisms such as auctions are being studied as an appropriate means for resource allocation in distributed and mulitagent decision problems. When agents value resources in combination rather than in isolation, they must often…

Artificial Intelligence · Computer Science 2013-01-30 Craig Boutilier , Moises Goldszmidt , Bikash Sabata

Textual explanations have proved to help improve user satisfaction on machine-made recommendations. However, current mainstream solutions loosely connect the learning of explanation with the learning of recommendation: for example, they are…

Information Retrieval · Computer Science 2021-01-26 Aobo Yang , Nan Wang , Hongbo Deng , Hongning Wang

This paper proposes a conceptual framework in which intelligence and consciousness emerge from relational structure rather than from prediction or domain-specific mechanisms. Intelligence is defined as the capacity to form and integrate…

Artificial Intelligence · Computer Science 2026-01-09 Sean Niklas Semmler

AI systems will soon have to navigate human environments and make decisions that affect people and other AI agents whose goals and values diverge. Contractualist alignment proposes grounding those decisions in agreements that diverse…

Equipping agents with the capacity to justify made decisions using supporting evidence represents a cornerstone of accountable decision-making. Furthermore, ensuring that justifications are in line with human expectations and societal norms…

Machine Learning · Computer Science 2024-02-27 Aleksa Sukovic , Goran Radanovic

We discuss the problem of defining a logic for analogical reasoning, and sketch a solution in the style of the semantics for Counterfactual Conditionals, Preferential Structures, etc.

Logic in Computer Science · Computer Science 2019-10-08 Karl Schlechta

Choice functions constitute a simple, direct and very general mathematical framework for modelling choice under uncertainty. In particular, they are able to represent the set-valued choices that appear in imprecise-probabilistic decision…

Artificial Intelligence · Computer Science 2019-05-22 Jasper De Bock , Gert de Cooman