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Goal-conditioned reinforcement learning endows an agent with a large variety of skills, but it often struggles to solve tasks that require more temporally extended reasoning. In this work, we propose to incorporate imagined subgoals into…

Machine Learning · Computer Science 2021-07-02 Elliot Chane-Sane , Cordelia Schmid , Ivan Laptev

Critical to successful human interaction is a capacity for empathy - the ability to understand and share the thoughts and feelings of another. As Artificial Intelligence (AI) systems are increasingly required to interact with humans in a…

Artificial Intelligence · Computer Science 2019-06-18 Maayan Shvo , Sheila A. McIlraith

In this paper, we discuss models of the common knowledge logic. The common knowledge logic is a multi-modal logic that includes the modal operators $\mathsf{K}_{i}$ ($i\in\mathcal{I}$, where $\mathcal{I}$ is a finite set of agents) and…

Logic · Mathematics 2025-12-23 Yoshihito Tanaka

The aim of this article is to generalize logics of formal inconsistency ($\textbf{LFI}$s) to systems dealing with the concept of incompatibility, expressed by means of a binary connective. The basic idea is that having two incompatible…

Logic · Mathematics 2022-02-23 Marcelo Esteban Coniglio , Guilherme Vicentin de Toledo

In this paper, we address the logic of knowing why, an example of a non-standard epistemic logic dealing with justified knowledge via a new epistemic operator, under the extensions with ideas from dynamic epistemic logic, namely public…

Logic · Mathematics 2018-09-24 Nicholas Pischke

Probability models have been proposed in the literature to account for "intelligent" behavior in many contexts. In this paper, probability propagation is applied to model agent's motion in potentially complex scenarios that include goals…

To coordinate with other systems, agents must be able to determine what the systems are currently doing and predict what they will be doing in the future---plan and goal recognition. There are many methods for plan and goal recognition, but…

Artificial Intelligence · Computer Science 2019-09-26 Christopher Amato , Andrea Baisero

We consider a pursuit-evasion scenario involving a group of pursuers and a single evader in a two-dimensional unbounded environment. The pursuers aim to capture the evader in finite time while ensuring the evader remains enclosed within the…

Systems and Control · Electrical Eng. & Systems 2026-05-25 Dinesh Patra , Prajakta Surve , Ashish R. Hota , Shaunak D. Bopardikar

Technological understanding is not a singular concept but varies depending on context. Building on De Jong and De Haro's (2025) notion of technological understanding as the ability to realise an aim through the use of a technological…

History and Philosophy of Physics · Physics 2026-04-27 Eline de Jong , Sebastian De Haro

Recent years witness a growing interest in nonstandard epistemic logics of "knowing whether", "knowing what", "knowing how", and so on. These logics are usually not normal, i.e., the standard axioms and reasoning rules for modal logic may…

Artificial Intelligence · Computer Science 2016-11-22 Tao Gu , Yanjing Wang

A temporally abstract action, or an option, is specified by a policy and a termination condition: the policy guides option behavior, and the termination condition roughly determines its length. Generally, learning with longer options (like…

Artificial Intelligence · Computer Science 2017-12-05 Anna Harutyunyan , Peter Vrancx , Pierre-Luc Bacon , Doina Precup , Ann Nowe

In a recent paper [Mar05] it is argued that to properly understand the thermodynamics of Landauer's Principle it is necessary extend the concept of logical operations to include indeterministic operations. Here we examine the thermodynamics…

Quantum Physics · Physics 2009-11-30 O. J. E. Maroney

The aim of this paper is to investigate the interplay between knowledge shared by a group of agents and its coalition ability. We investigate this relation in the standard context of imperfect information concurrent game. We assume that…

Artificial Intelligence · Computer Science 2016-11-28 Guifei Jiang , Dongmo Zhang , Laurent Perrussel

The framework of algorithmic knowledge assumes that agents use deterministic knowledge algorithms to compute the facts they explicitly know. We extend the framework to allow for randomized knowledge algorithms. We then characterize the…

Artificial Intelligence · Computer Science 2017-01-11 Joseph Y. Halpern , Riccardo Pucella

Information based thermodynamic logic is revisited. It consists of two parts: Part A applies the modern theory of probability in which an arbitrary convex function \phi is employed as an analytic "device" to express information as…

Statistical Mechanics · Physics 2023-12-07 Bing Miao , Hong Qian , Yong-Shi Wu

Agents can achieve effective interaction with previously unknown other agents by maintaining beliefs over a set of hypothetical behaviours, or types, that these agents may have. A current limitation in this method is that it does not…

Multiagent Systems · Computer Science 2019-06-27 Stefano V. Albrecht , Peter Stone

An agent that efficiently accumulates knowledge to develop increasingly sophisticated skills over a long lifetime could advance the frontier of artificial intelligence capabilities. The design of such agents, which remains a long-standing…

Machine Learning · Computer Science 2025-06-27 Saurabh Kumar , Henrik Marklund , Ashish Rao , Yifan Zhu , Hong Jun Jeon , Yueyang Liu , Benjamin Van Roy

Integrated information theory is a mathematical, quantifiable theory of conscious experience. The linchpin of this theory, the $\phi$ measure, quantifies a system's irreducibility to disjoint parts. Purely as a measure of irreducibility, we…

Information Theory · Computer Science 2014-10-10 Virgil Griffith

The CAP theorem asserts a trilemma between consistency, availability, and partition tolerance. This paper introduces a rigorous automata-theoretic and economically grounded framework that reframes the CAP trade-off as a constraint…

Computer Science and Game Theory · Computer Science 2025-07-04 Craig S Wright

Accurately modeling pedestrian intention and understanding driver decision-making processes are critical for the development of safe and socially aware autonomous driving systems. We introduce PSI, a benchmark dataset that captures the…

Computer Vision and Pattern Recognition · Computer Science 2026-04-27 Taotao Jing , Tina Chen , Renran Tian , Yaobin Chen , Joshua Domeyer , Heishiro Toyoda , Rini Sherony , Zhengming Ding
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