Proceedings Eighteenth Conference on Theoretical Aspects of Rationality and Knowledge

• URL: http://arxiv.org/abs/2106.10886v1
• Date: Mon, 21 Jun 2021 07:01:14 GMT
• Title: Proceedings Eighteenth Conference on Theoretical Aspects of Rationality and Knowledge
• Authors: Joseph Halpern (Cornell University), Andr\'es Perea (Maastricht University)
• Abstract summary: The TARK conference (Theoretical Aspects of Rationality and Knowledge) is a biannual conference that aims to bring together researchers from a wide variety of fields. Its goal is to further our understanding of interdisciplinary issues involving reasoning about rationality and knowledge. Papers have been accepted for presentation at the Eighteenth Conference on Theoretical Aspects of Rationality and Knowledge (TARK 2021), held between June 25 and June 27, 2021, at Tsinghua University at Beijing, China.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The TARK conference (Theoretical Aspects of Rationality and Knowledge) is a biannual conference that aims to bring together researchers from a wide variety of fields, including computer science, artificial intelligence, game theory, decision theory, philosophy, logic, linguistics, and cognitive science. Its goal is to further our understanding of interdisciplinary issues involving reasoning about rationality and knowledge. Topics of interest include, but are not limited to, semantic models for knowledge, belief, awareness and uncertainty, bounded rationality and resource-bounded reasoning, commonsense epistemic reasoning, epistemic logic, epistemic game theory, knowledge and action, applications of reasoning about knowledge and other mental states, belief revision, and foundations of multi-agent systems. These proceedings contain the papers that have been accepted for presentation at the Eighteenth Conference on Theoretical Aspects of Rationality and Knowledge (TARK 2021), held between June 25 and June 27, 2021, at Tsinghua University at Beijing, China.

Related papers

• Proceedings of the 21st International Conference on Quantum Physics and Logic [49.1574468325115]
  QPL is an annual conference that brings together academic and industry researchers working on the mathematical foundations of quantum computation, quantum physics, and related areas. The main focus is on the use of algebraic and categorical structures, formal languages, semantic methods, as well as other mathematical and computer scientific techniques applicable to the study of physical systems, physical processes, and their composition.
  arXiv  Detail & Related papers  (2024-08-09T15:04:17Z)
• Proceedings Nineteenth conference on Theoretical Aspects of Rationality and Knowledge [0.0]
  TARK conference aims to bring together researchers from a wide variety of fields. Previous conferences have been held biennially around the world since 1986.
  arXiv  Detail & Related papers  (2023-07-08T16:22:42Z)
• Foundations and Recent Trends in Multimodal Machine Learning: Principles, Challenges, and Open Questions [68.6358773622615]
  This paper provides an overview of the computational and theoretical foundations of multimodal machine learning. We propose a taxonomy of 6 core technical challenges: representation, alignment, reasoning, generation, transference, and quantification. Recent technical achievements will be presented through the lens of this taxonomy, allowing researchers to understand the similarities and differences across new approaches.
  arXiv  Detail & Related papers  (2022-09-07T19:21:19Z)
• Acquiring and Modelling Abstract Commonsense Knowledge via Conceptualization [49.00409552570441]
  We study the role of conceptualization in commonsense reasoning, and formulate a framework to replicate human conceptual induction. We apply the framework to ATOMIC, a large-scale human-annotated CKG, aided by the taxonomy Probase.
  arXiv  Detail & Related papers  (2022-06-03T12:24:49Z)
• A Quantitative Symbolic Approach to Individual Human Reasoning [0.0]
  We take findings from the literature and show how these, formalized as cognitive principles within a logical framework, can establish a quantitative notion of reasoning. We employ techniques from non-monotonic reasoning and computer science, namely, a solving paradigm called answer set programming (ASP) Finally, we can fruitfully use plausibility reasoning in ASP to test the effects of an existing experiment and explain different majority responses.
  arXiv  Detail & Related papers  (2022-05-10T16:43:47Z)
• Active Inference in Robotics and Artificial Agents: Survey and Challenges [51.29077770446286]
  We review the state-of-the-art theory and implementations of active inference for state-estimation, control, planning and learning. We showcase relevant experiments that illustrate its potential in terms of adaptation, generalization and robustness.
  arXiv  Detail & Related papers  (2021-12-03T12:10:26Z)
• Computational Argumentation and Cognition [0.3867363075280543]
  This paper stems from the 1st Workshop on Computational Argumentation and Cognition (COGNITAR) It argues that within the context of Human-Centric AI the use of theory and methods from Computational Argumentation for the study of Cognition can be a promising avenue to pursue. The paper presents the main problems and challenges in the area that would need to be addressed, both at the scientific level but also at the level of synthesis of ideas and approaches from the various disciplines involved.
  arXiv  Detail & Related papers  (2021-11-12T21:44:30Z)
• A Mathematical Walkthrough and Discussion of the Free Energy Principle [0.0]
  The Free-Energy-Principle (FEP) is an influential and controversial theory which postulates a connection between the thermodynamics of self-organization and learning through variational inference. FEP has been applied extensively in neuroscience, and is beginning to make inroads in machine learning by spurring the construction of novel and powerful algorithms by which action, perception, and learning can all be unified under a single objective. Here, we aim to provide a mathematically detailed, yet intuitive walk-through of the formulation and central claims of the FEP while also providing a discussion of the assumptions necessary and potential limitations of the theory.
  arXiv  Detail & Related papers  (2021-08-30T16:11:49Z)
• The General Theory of General Intelligence: A Pragmatic Patternist Perspective [0.0]
  Review covers underlying philosophies, formalizations of the concept of intelligence, and a proposed high level architecture for AGI systems. The specifics of human-like cognitive architecture are presented as manifestations of these general principles. Lessons for practical implementation of advanced AGI in frameworks such as OpenCog Hyperon are briefly considered.
  arXiv  Detail & Related papers  (2021-03-28T10:11:25Z)
• Formalising Concepts as Grounded Abstractions [68.24080871981869]
  This report shows how representation learning can be used to induce concepts from raw data. The main technical goal of this report is to show how techniques from representation learning can be married with a lattice-theoretic formulation of conceptual spaces.
  arXiv  Detail & Related papers  (2021-01-13T15:22:01Z)
• Neuro-symbolic Architectures for Context Understanding [59.899606495602406]
  We propose the use of hybrid AI methodology as a framework for combining the strengths of data-driven and knowledge-driven approaches. Specifically, we inherit the concept of neuro-symbolism as a way of using knowledge-bases to guide the learning progress of deep neural networks.
  arXiv  Detail & Related papers  (2020-03-09T15:04:07Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.