[SydPhil] Fw: HPS Research Seminar, Monday 4, March 2024 at 5:30pm (Please ignore this is incorrect advert for 4 March 2024))

[HPS Admin]

Dear All

Apologies, this is the incorrect Seminar advert for the 4th March 2024 HPS seminar.

The corrected version will be sent out shortly.

Regards

Cynthia


CYNTHIA KIU | EXECUTIVE OFFICER
The University of Sydney
Faculty of Science, History and Philosophy of Science

Rm No 389, Carslaw F07 | The University of Sydney | NSW | 2006
+61 2 9351 4161
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OFFICE HOURS ARE MONDAY, TUESDAY AND WEDNESDAY

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________________________________
From: Cynthia Kiu on behalf of HPS Admin <hps.admin at sydney.edu.au>
Sent: Tuesday, February 27, 2024 10:04 AM
To: (sydphil at arts.usyd.edu.au) <sydphil at arts.usyd.edu.au>
Subject: HPS Research Seminar, Monday 4, March 2024 at 5:30pm


School of History and Philosophy of Science
RESEARCH SEMINAR
[The University of Sydney]
[https://d31hzlhk6di2h5.cloudfront.net/20240226/cb/75/e2/c4/b84bae4efd3f95e0a8dd36fd_360x512.png]
The Liar paradox, the halting problem and the edge of chaos
Mikhail Prokopenko (USyd)

Dates: Monday, 04/03/2024
Time: 5:30pm
Venue: New Law (F10), Level 3, Seminar Room 344
How to register: Free, no registration required

Abstract: We will explore several fundamental relations between formal systems, algorithms, and dynamical systems, focussing on the roles of self-reference and computational undecidability. This comparative analysis will emphasise three factors: (i) the program-data duality; (ii) the potential to access an infinite computational medium; and (iii) the ability to implement negation. Importantly, the program-data duality requires that a computational agent must be able to store and process encoded information, as well as create self-referential meta-level simulations. Finally, within Gödel – Turing – Post framework, we will argue that undecidability leads to novelty generation, via the emergence of functional self-descriptions across major transitions: genetic, linguistic and cultural.


Bio: Prof. Mikhail Prokopenko leads the Centre for Complex Systems at the University of Sydney. He holds PhD in Computer Science, MA in Economics, and MSc in Applied Mathematics. Mikhail has a strong international reputation in modelling and simulation of complex self-organising systems, with over 200 publications and h-index of 43. His cross-disciplinary research in information theory, critical phenomena and artificial intelligence has been applied to pandemic and crisis modelling, systems biology, urban dynamics, and other diverse areas.

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