Account
Orders
Advanced search
From a Philosophical Perspective
Louise Reader
Read on Louise Reader App.
How can we teach machine learning to identify causal patterns in data? This book explores the very notion of “causality”, identifying from a naturalistic and evolutionary perspective how living systems deal with causal relationships. At the same time, using this knowledge to identify the best ways to apply such biological models in machine learning scenarios.
One of the more fundamental challenges for AI experts is to design machines that can understand the world, identifying the basic rules that govern reality. Statistics are powerful and fundamental for this process, but they are only one of the necessary tools. Counterfactual thinking is the other part of the necessary process that will help machines to become intelligent. This book explains the paths that can lead to algorithmic causality.
It is essential reading for those who are not afraid of thinking at the interface of various academic disciplines or fields (AI, machine learning, philosophy, neuroscience, anthropology, psychology, computer sciences), and who are interested in the analysis of causal thinking and the ways in which cognitive systems (natural or artificial) can act in order to understand their environment.
Professor Vallverdú is currently working on biomimetic cognitive architectures and multicognitive systems. His research has explored two main areas: epistemology and cognition. Since his early Ph.D. research on epistemic controversies, he has analyzed several aspects of computational epistemology.
His latest research has focused on the causal challenges of machine learning techniques, particularly deep learning. One of his most promising advances is statistics meets causal graph reasoning (via Directed Acyclic Graphs), which still has several conceptual paths that need to be explored and identified. Counterfactual reasoning is a fundamental part of these open debates, which are under the analysis of Prof. Vallverdú.
His current research is supported as part of the following projects: GEHUCT and ICREA Acadèmia.
Les livres numériques peuvent être téléchargés depuis l'ebookstore Numilog ou directement depuis une tablette ou smartphone.
PDF : format reprenant la maquette originale du livre ; lecture recommandée sur ordinateur et tablette EPUB : format de texte repositionnable ; lecture sur tous supports (ordinateur, tablette, smartphone, liseuse)
DRM Adobe LCP
LCP DRM Adobe
This ebook is DRM protected.
LCP system provides a simplified access to ebooks: an activation key associated with your customer account allows you to open them immediately.
ebooks downloaded with LCP system can be read on:
Adobe DRM associates a file with a personal account (Adobe ID). Once your reading device is activated with your Adobe ID, your ebook can be opened with any compatible reading application.
ebooks downloaded with Adobe DRM can be read on:
mobile-and-tablet To check the compatibility with your devices,see help page
Prof. Dr. Jordi Vallverdú, Ph.D., M.Sci., B.Mus, B.Phil, is Tenure Professor (Accredited Full Professor) at Universitat Autònoma de Barcelona (Catalonia, Spain), where he teaches philosophy and history of science and computing. His research focuses on the cognitive and epistemic aspects of the philosophy of computing, philosophy of science, and AI, with a special interest in emotional modeling. He was recently awarded an ICREA grant for Causality in Deep Learning. In 2011, he won a Japanese JSPS fellowship to pursue research on computational HRI interfaces at Nishidalab, Kyoto University. He has written and edited more than 15 books, including: (2009) Handbook of Research on Synthetic Emotions and Sociable Robotics: New Applications in Affective Computing and AI; (2010) Thinking Machines and the Philosophy of Computer Science: Concepts and Principles; (2012) Creating Synthetic Emotions Through Technological and Robotic Advancements; (2015) Synthesizing Human Emotion in Intelligent Systems and Robotics; (2016) Bayesians Versus Frequentists. A Philosophical Debate on Statistical Reasoning; and (2019) Blended Cognition. The Robotic Challenge; and (2023) Gender in AI and Robotics. The Gender Challenges from an Interdisciplinary Perspective.
Sign up to get our latest ebook recommendations and special offers