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We introduce games with probabilistic uncertainty, a natural model for controller synthesis in which the controller observes the state of the system through imprecise sensors that provide correct information about the current state with a…

Computer Science and Game Theory · Computer Science 2012-07-03 Krishnendu Chatterjee , Martin Chmelik , Rupak Majumdar

We investigate indeterminism in physical observations. For this, we introduce a distinction between genuinely indeterministic (creation-1 and discovery-1) observational processes, and fully deterministic (creation-2 and discovery-2)…

Quantum Physics · Physics 2015-02-17 Massimiliano Sassoli de Bianchi

At the beginning of a dynamic game, players may have exogenous theories about how the opponents are going to play. Suppose that these theories are commonly known. Then, players will refine their first-order beliefs, and challenge their own…

Computer Science and Game Theory · Computer Science 2017-07-28 Emiliano Catonini

Soft set theory provides a direct framework for parameterized decision modeling by assigning to each attribute (parameter) a subset of a given universe, thereby representing uncertainty in a structured way [1, 2]. Over the past decades, the…

Artificial Intelligence · Computer Science 2026-03-17 Takaaki Fujita , Florentin Smarandache

This paper presents a plausible reasoning system to illustrate some broad issues in knowledge representation: dualities between different reasoning forms, the difficulty of unifying complementary reasoning styles, and the approximate nature…

Artificial Intelligence · Computer Science 2013-03-26 Wray L. Buntine

We survey recent developments in the study of probabilistic complexity classes. While the evidence seems to support the conjecture that probabilism can be deterministically simulated with relatively low overhead, i.e., that $P=BPP$, it also…

Computational Complexity · Computer Science 2008-12-15 Russell Impagliazzo

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 typically arise from applying decision rules…

Artificial Intelligence · Computer Science 2018-06-05 Jasper De Bock , Gert de Cooman

Determinism is (roughly) the thesis that the past determines the future. But efforts to define it precisely have exposed deep methodological disagreements. Standard possible-worlds formulations of determinism presuppose an "agreement"…

History and Philosophy of Physics · Physics 2026-01-19 Hans Halvorson , JB Manchak , James Owen Weatherall

An approach is presented treating decision theory as a probabilistic theory based on quantum techniques. Accurate definitions are given and thorough analysis is accomplished for the quantum probabilities describing the choice between…

Artificial Intelligence · Computer Science 2022-06-06 V. I. Yukalov

Analyzing decision problems under uncertainty commonly relies on idealizing assumptions about the describability of the world, with the most prominent examples being the closed world and the small world assumption. Most assumptions are…

Methodology · Statistics 2025-12-08 Christoph Jansen , Georg Schollmeyer , Thomas Augustin , Julian Rodemann

Tests of Bell's theorem rule out local hidden variables theories. But any theorem is only as good as the assumptions that go into it, and one of these assumptions is that the experimenter can freely chose the detector settings. Without this…

Quantum Physics · Physics 2015-06-18 Sabine Hossenfelder

In contrast to the usual understanding of probabilistic systems as stochastic processes, recently these systems have also been regarded as transformers of probabilities. In this paper, we give a natural definition of strong bisimulation for…

Logic in Computer Science · Computer Science 2014-05-12 Holger Hermanns , Jan Krčál , Jan Křetínský

Probability theory as extended logic is completed such that essentially any probability may be determined. This is done by considering propositional logic (as opposed to predicate logic) as syntactically suffcient and imposing a symmetry…

Statistics Theory · Mathematics 2014-08-12 Cael L. Hasse

Artificial intelligence commonly refers to the science and engineering of artificial systems that can carry out tasks generally associated with requiring aspects of human intelligence, such as playing games, translating languages, and…

Artificial Intelligence · Computer Science 2025-02-11 Andreas Krause , Jonas Hübotter

This paper presents a theory of systemic undecidability, reframing incomputability as a structural property of systems rather than a localized feature of specific functions or problems. We define a notion of causal embedding and prove a…

Logic in Computer Science · Computer Science 2025-09-03 Seth Bulin

In this paper we introduce the reactivity in decision-form games. The concept of reactivity allows us to give a natural concept of rationalizable solution for decision-form games: the solubility by elimination of sub-reactive strategies.…

Adaptation and Self-Organizing Systems · Physics 2011-03-07 David Carfì

We outline how to create a mechanism that provides an optimal way to elicit, from an arbitrary group of experts, the probability of the truth of an arbitrary logical proposition together with collective information that has an explicit form…

Computer Science and Game Theory · Computer Science 2023-09-04 Alexey V. Osipov , Nikolay N. Osipov

This position paper reflects on the state-of-the-art in decision-making under uncertainty. A classical assumption is that probabilities can sufficiently capture all uncertainty in a system. In this paper, the focus is on the uncertainty…

Artificial Intelligence · Computer Science 2023-03-13 Thom Badings , Thiago D. Simão , Marnix Suilen , Nils Jansen

In this paper we introduce polytopal stochastic games, an extension of two-player, zero-sum, turn-based stochastic games, in which we may have uncertainty over the transition probabilities. In these games the uncertainty over the…

Logic in Computer Science · Computer Science 2025-02-26 Pablo F. Castro , Pedro D'Argenio

An inductive logic can be formulated in which the elements are not propositions or probability distributions, but information systems. The logic is complete for information systems with binary hypotheses, i.e., it applies to all such…

Artificial Intelligence · Computer Science 2013-04-11 Norman C. Dalkey