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I explain the shutdown problem: the problem of designing artificial agents that (1) shut down when a shutdown button is pressed, (2) don't try to prevent or cause the pressing of the shutdown button, and (3) otherwise pursue goals…

Artificial Intelligence · Computer Science 2024-04-10 Elliott Thornley

In this paper a conditional logic is defined and studied. This conditional logic, Deterministic Bayesian Logic, is constructed as a deterministic counterpart to the (probabilistic) Bayesian conditional. The logic is unrestricted, so that…

Logic in Computer Science · Computer Science 2011-11-09 Frederic Dambreville

We argue that an explainable artificial intelligence must possess a rationale for its decisions, be able to infer the purpose of observed behaviour, and be able to explain its decisions in the context of what its audience understands and…

Artificial Intelligence · Computer Science 2021-04-26 Michael Timothy Bennett , Yoshihiro Maruyama

The ability to invent new tools has been identified as an important facet of our ability as a species to problem solve in dynamic and novel environments. While the use of tools by artificial agents presents a challenging task and has been…

Artificial Intelligence · Computer Science 2023-11-08 Poppy Collis , Paul F Kinghorn , Christopher L Buckley

Conway and Kochen's Free Will Theory is examined as an important foundational element in a new area of activity in computer science - developing protocols for quantum computing

History and Philosophy of Physics · Physics 2016-04-25 Ilyas Khan

Most physics theories are deterministic, with the notable exception of quantum mechanics which, however, comes plagued by the so-called measurement problem. This state of affairs might well be due to the inability of standard mathematics to…

History and Philosophy of Physics · Physics 2021-11-04 Nicolas Gisin

Is there a canonical way to think of agency beyond reward maximisation? In this paper, we show that any type of behaviour complying with physically sound assumptions about how macroscopic biological agents interact with the world…

Artificial Intelligence · Computer Science 2024-01-24 Lancelot Da Costa , Samuel Tenka , Dominic Zhao , Noor Sajid

The concept of the 'agent' has profoundly shaped Artificial Intelligence (AI) research, guiding development from foundational theories to contemporary applications like Large Language Model (LLM)-based systems. This paper critically…

Artificial Intelligence · Computer Science 2025-09-16 Jesse Gardner , Vladimir A. Baulin

It is clear that one of the primary tools we can use to mitigate the potential risk from a misbehaving AI system is the ability to turn the system off. As the capabilities of AI systems improve, it is important to ensure that such systems…

Artificial Intelligence · Computer Science 2017-06-19 Dylan Hadfield-Menell , Anca Dragan , Pieter Abbeel , Stuart Russell

The concept of rationality is central to the field of artificial intelligence (AI). Whether we are seeking to simulate human reasoning, or trying to achieve bounded optimality, our goal is generally to make artificial agents as rational as…

Artificial Intelligence · Computer Science 2025-09-05 Olivia Macmillan-Scott , Mirco Musolesi

The arrival of Large Language Models (LLMs) has stirred up philosophical debates about the possibility of realizing agency in an artificial manner. In this work we contribute to the debate by presenting a theoretical model that can be used…

Artificial Intelligence · Computer Science 2024-07-25 Maud van Lier , Gorka Muñoz-Gil

We provide a reinterpretation of the quantum vacuum ambiguities that one encounters when studying particle creation phenomena due to an external and time-dependent agent. We propose a measurement-motivated understanding: Each way of…

The pursuit of general intelligence has traditionally centered on external objectives: an agent's control over its environments or mastery of specific tasks. This external focus, however, can produce specialized agents that lack…

Machine Learning · Computer Science 2025-07-31 Hanqi Zhou , Fryderyk Mantiuk , David G. Nagy , Charley M. Wu

Decision theorists propose a normative theory of rational choice. Traditionally, they assume that they should provide some constant and invariant principles as criteria for rational decisions, and indirectly, for agents. They seek a…

General Economics · Economics 2021-01-25 Saleh Afroogh

In a strategy-proof mechanism, the influence of an agent may be measured as the set of outcomes an agent can bring about by varying her (reported) type. More specifically, we refer to an agent's influence on her own relevant outcomes as her…

Theoretical Economics · Economics 2025-12-12 Christian Basteck , Ulysse Lojkine

This essay addresses the implications of integrated information theory (IIT) for free will. IIT is a theory of what consciousness is and what it takes to have it. According to IIT, the presence of consciousness is accounted for by a maximum…

Neurons and Cognition · Quantitative Biology 2023-04-04 Giulio Tononi , Larissa Albantakis , Melanie Boly , Chiara Cirelli , Christof Koch

This paper argues that model-free reinforcement learning (RL) agents, while lacking explicit planning mechanisms, exhibit behaviours that can be analogised to System 1 ("thinking fast") processes in human cognition. Unlike model-based RL…

Artificial Intelligence · Computer Science 2025-01-31 Hal Ashton , Matija Franklin

Conditional independence is a crucial concept supporting adequate modelling and efficient reasoning in probabilistics. In knowledge representation, the idea of conditional independence has also been introduced for specific formalisms, such…

Artificial Intelligence · Computer Science 2024-12-19 Jesse Heyninck

A tradition handed down among physicists maintains that classical physics is a perfectly deterministic theory capable of predicting the future with absolute certainty, independently of any interpretations. It also tells that it was quantum…

History and Philosophy of Physics · Physics 2023-03-09 Flavio Del Santo

An agent acquires a costly flexible signal before making a decision. We explore to what degree knowledge of the agent's information costs helps predict her behavior. We establish an impossibility result: learning costs alone generate no…

Theoretical Economics · Economics 2023-04-05 Elliot Lipnowski , Doron Ravid
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