1.

Record Nr.

UNINA9910781379903321

Autore

Dunker Christian

Titolo

The Constitution of the Psychoanalytic Clinic : A History of its Structure and Power / / by Christian Dunker

Pubbl/distr/stampa

Boca Raton, FL : , : Routledge, , [2018]

©2011

ISBN

0-429-92035-0

0-429-48135-7

1-283-07103-7

9786613071033

1-84940-736-3

Edizione

[First edition.]

Descrizione fisica

1 online resource (613 p.)

Collana

Lines of the symbolic series

Disciplina

150.195

Soggetti

Psychoanalysis - History

Psychiatry - History

Psychiatric clinics - History

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references (p. 373-391) and index.

Nota di contenuto

Cover; Copyright; Contents; Preface; Acknowledgements; Note on References; Introduction; Chapter One: The doubt of Ulysses; Chapter Two: The return of Empedocles; Chapter Three: The act of Antigone; Chapter Four: Rhetoric of space, rhetoric of time: paradox and interpretation; Chapter Five: Taking care of oneself; Chapter Six: Montaigne, the most sceptical of the hysterics; Chapter Seven: The meditation of Descartes; Chapter Eight: The structure of psychoanalytic treatment; Chapter Nine: Kant and the pathological; Chapter Ten: The rebirth of the clinic as structure and as experience

Chapter Eleven: Hegel: the real and its negativeChapter Twelve: Logic and politics in psychoanalytic healing; Conclusion; References

Sommario/riassunto

This book provides a detailed examination of the historical roots of psychoanalysis from ancient Greece to the late nineteenth century, focusing on social practices that were related to the founders of psychoanalytic theory and maintained within contemporary treatment. Alongside the reconstruction of an evolutionary accumulation of



healing practices, the book includes linked discussions of current issues pertaining to psychoanalytic treatment and its working structure as elaborated by Freud and Lacan. There are vital political consequences for psychoanalytic practice - here articulated with an acknowledgement of these practical derivations of early pre-psychoanalytic treatments of the soul. The book demonstrates that these are neither mere techniques nor concepts of the world and the human subject, but they concern the way the problem of power is articulated. The historical establishment of psychoanalytical practice becomes legible through analysis of the traces of the elements of a political ontology, an account of the roots of those traces and the elaboration of the conceptual structure of psychoanalysis as theory and treatment, a praxis which maintains its own distinctive identity.

2.

Record Nr.

UNISALENTO991004403228307536

Autore

Zhao, Shiyu

Titolo

Mathematical foundations of reinforcement learning / by Shiyu Zhao

Pubbl/distr/stampa

Singapore : Springer Nature Singapore

Tsinghua : Tsinghua University Press, 2025

ISBN

9789819739448

Descrizione fisica

xvi, 275 p. ; 25 cm

Classificazione

AMS 68T

Disciplina

006.3

Soggetti

Artificial intelligence

Machine learning

Artificial intelligence - Data processing

Multiagent systems

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

1 Basic Concepts -- 2 State Value and Bellman Equation -- 3 Optimal State Value and Bellman Optimality Equation -- 4 Value Iteration and Policy Iteration -- 5 Monte Carlo Learning -- 6 Stochastic Approximation -- 7 Temporal-Difference Learning -- 8 Value Function Approximation -- 9 Policy Gradient -- 10 Actor-Critic Methods



Sommario/riassunto

This book provides a mathematical yet accessible introduction to the fundamental concepts, core challenges, and classic reinforcement learning algorithms. It aims to help readers understand the theoretical foundations of algorithms, providing insights into their design and functionality. Numerous illustrative examples are included throughout. The mathematical content is carefully structured to ensure readability and approachability. The book is divided into two parts. The first part is on the mathematical foundations of reinforcement learning, covering topics such as the Bellman equation, Bellman optimality equation, and stochastic approximation. The second part explicates reinforcement learning algorithms, including value iteration and policy iteration, Monte Carlo methods, temporal-difference methods, value function methods, policy gradient methods, and actor-critic methods. With its comprehensive scope, the book will appeal to undergraduate and graduate students, post-doctoral researchers, lecturers, industrial researchers, and anyone interested in reinforcement learning