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AI3SD Video: The Bluffers Guide to Symbolic AI

AI3SD Video: The Bluffers Guide to Symbolic AI
AI3SD Video: The Bluffers Guide to Symbolic AI
Symbolic AI, sometimes referred to as Good Old-fashioned AI, has its roots in the earliest days of the AI project. It seeks to represent reasoning using explicit data structures often drawn from logic. Symbolic AI systems have the advantage of being comparatively easy to understand and analyse and potentially allow compact forms of representation and communication. Their disadvantages tend to include inflexibility, a high knowledge engineering cost, and difficulty handling non-symbolic, statistical and analogue processes such as vision and motion. This talk will cover a brief history of the field and current topics within it as well as looking at proposals for combining symbolic and non-symbolic reasoning.
AI, AI3SD Event, Artificial Intelligence, Ontologies, OWL, Semantic Web, Semantics, Symbolic AI
Dennis, Louise
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Kanza, Samantha
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Frey, Jeremy G.
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Niranjan, Mahesan
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Hooper, Victoria
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Dennis, Louise
e772a6a8-b1a1-4d2c-9d1c-056088f624e7
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Hooper, Victoria
af1a99f1-7848-4d5c-a4b5-615888838d84

Dennis, Louise (2020) AI3SD Video: The Bluffers Guide to Symbolic AI. Kanza, Samantha, Frey, Jeremy G., Niranjan, Mahesan and Hooper, Victoria (eds.) AI3SD Summer Seminar Series 2020, Online, Southampton, United Kingdom. 01 Jul - 23 Sep 2020. (doi:10.5258/SOTON/P0058).

Record type: Conference or Workshop Item (Other)

Abstract

Symbolic AI, sometimes referred to as Good Old-fashioned AI, has its roots in the earliest days of the AI project. It seeks to represent reasoning using explicit data structures often drawn from logic. Symbolic AI systems have the advantage of being comparatively easy to understand and analyse and potentially allow compact forms of representation and communication. Their disadvantages tend to include inflexibility, a high knowledge engineering cost, and difficulty handling non-symbolic, statistical and analogue processes such as vision and motion. This talk will cover a brief history of the field and current topics within it as well as looking at proposals for combining symbolic and non-symbolic reasoning.

Video
AI3SDOnlineSeminarSeries-9-LD-020920 - Version of Record
Available under License Creative Commons Attribution.
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More information

Published date: 2 September 2020
Additional Information: Louise is a senior lecturer at the University of Manchester where she is part of the Autonomy and Verification group. She is a member of the IEEE Global Initiative for Ethical Considerations in the Design of Autonomous Systems and the IEEE Standards working group for Transparency for Autonomous Systems (P7001). She is currently co-investigator on two EPSRC Hubs for Robotics in Extreme and Challenging Environments: Future AI and Robotics for Space (FAIR-SPACE) and Robotics and AI for Nuclear (RAIN). Her expertise is in the development and verification of autonomous systems with interests in rational agent programming languages, and architectures for autonomous systems, with a particular emphasis on ethical machine reasoning and creating verifiable systems.
Venue - Dates: AI3SD Summer Seminar Series 2020, Online, Southampton, United Kingdom, 2020-07-01 - 2020-09-23
Keywords: AI, AI3SD Event, Artificial Intelligence, Ontologies, OWL, Semantic Web, Semantics, Symbolic AI

Identifiers

Local EPrints ID: 447164
URI: http://eprints.soton.ac.uk/id/eprint/447164
PURE UUID: ea5f2abc-773b-4cf2-b874-8ca5363a3c92
ORCID for Samantha Kanza: ORCID iD orcid.org/0000-0002-4831-9489
ORCID for Jeremy G. Frey: ORCID iD orcid.org/0000-0003-0842-4302
ORCID for Mahesan Niranjan: ORCID iD orcid.org/0000-0001-7021-140X

Catalogue record

Date deposited: 04 Mar 2021 17:39
Last modified: 17 Mar 2024 03:51

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Contributors

Author: Louise Dennis
Editor: Samantha Kanza ORCID iD
Editor: Jeremy G. Frey ORCID iD
Editor: Mahesan Niranjan ORCID iD
Editor: Victoria Hooper

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