In Naturally Free Action, Oisín Deery argues that free will exists, where free will is understood as the ability to act freely, and free actions as exercises of that ability. Deery reaches his conclusion by showing how the concept of free will plausibly refers to many actual human behaviors, and how these behaviors count as a natural category or kind. Deery also addresses the role of phenomenology in fixing the reference of the concept, arguing that our phenomenology as of deciding or acting freely is typically accurate, even if determinism is true. The result is a realist, naturalistic framework for theorizing about free will, according to which free will almost certainly exists and we act freely. Deery's position mostly sidesteps the question of whether free will is compatible with determinism. Even so, Deery maintains that his natural-kind view about free will supports compatibilism and provides compatibilists with an attractive way to be realists about free will. Deery also responds to recent empirical threats to free will, including those posed by findings about behaviors caused by implicit biases. Finally, Deery shows how his view possesses the resources to address emerging questions about whether artificially intelligent agents might ever act freely or be responsible for their behaviors, and if so in what sense.

In Naturally Free Action, Oisin Deery argues that free will exists, where free will is understood as the ability to act freely, and free actions as exercises of that ability. This conclusion is supported by showing how the concept of free will plausibly refers to many actual human behaviors,and how these behaviors count as a natural category or kind. Deery also addresses the role of phenomenology in fixing the reference of the concept, arguing that our phenomenology as of deciding or acting freely is typically accurate, even if determinism is true. The result is a realist, naturalisticframework for theorizing about free will, according to which free will almost certainly exists and we act freely. This verdict mostly sidesteps the compatibility question, which asks whether free will is compatible with determinism. Even so, Deery maintains that the natural-kind view about free willsupports compatibilism and provides compatibilists with an attractive way to be realists about free will. Additionally, the book argues that this view has the resources to respond to recent empirical threats to free will, including those posed by findings about behaviors caused by implicit biases.Finally, Deery demonstrates how the natural-kind view has the resources to address emerging questions about whether artificially intelligent agents might ever act freely or be responsible for their behaviors, and if so in what sense.

In 'Naturally Free Action', Oisâin Deery argues that free will exists, understood as the ability to act freely. This conclusion is supported by showing how the concept of free will plausibly refers to many actual human behaviours, and how these behaviours count as a natural category or kind.

From a moral point of view we think of ourselves as capable of responsible actions. From a scientific point of view we think of ourselves as animals whose behavior, however highly evolved, conforms to natural scientific laws. Natural Agency argues that these different perspectives can be reconciled, despite the skepticism of many philosophers who have argued that "free will" is impossible under "scientific determinism." This skepticism is best overcome according to the author, by defending a causal theory of action, that is by establishing that actions are constituted by behavioral events with the appropriate kind of mental causal history. He sets out a rich and subtle argument for such a theory and defends it against its critics. Thus the book demonstrates the importance of philosophical work in action theory for the central metaphysical task of understanding our place in nature.

Action selection is the task of doing the right thing at the right time. It requires the assessment of available alternatives, executing those most appropriate, and resolving conflicts among competing goals and possibilities. Using advanced computational modelling, this book explores cutting-edge research into action selection in nature from a wide range of disciplines, from neuroscience to behavioural ecology, and even political science. It delivers new insights into both detailed and systems-level attributes of natural intelligence and demonstrates advances in methodological practice. Contributions from leading researchers cover issues including whether biological action selection is optimal, neural substrates for action selection in the vertebrate brain, perceptual selection in decision making, and interactions between group and individual action selection. This first integrated review of action selection in nature contains a balance of review and original research material, consolidating current knowledge into a valuable reference for researchers while illustrating potential paths for future studies.

Summary Natural Language Processing in Action is your guide to creating machines that understand human language using the power of Python with its ecosystem of packages dedicated to NLP and AI. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Recent advances in deep learning empower applications to understand text and speech with extreme accuracy. The result? Chatbots that can imitate real people, meaningful resume-to-job matches, superb predictive search, and automatically generated document summaries—all at a low cost. New techniques, along with accessible tools like Keras and TensorFlow, make professional-quality NLP easier than ever before. About the Book Natural Language Processing in Action is your guide to building machines that can read and interpret human language. In it, you'll use readily available Python packages to capture the meaning in text and react accordingly. The book expands traditional NLP approaches to include neural networks, modern deep learning algorithms, and generative techniques as you tackle real-world problems like extracting dates and names, composing text, and answering free-form questions. What's inside Some sentences in this book were written by NLP! Can you guess which ones? Working with Keras, TensorFlow, gensim, and scikit-learn Rule-based and data-based NLP Scalable pipelines About the Reader This book requires a basic understanding of deep learning and intermediate Python skills. About the Author Hobson Lane, Cole Howard, and Hannes Max Hapke are experienced NLP engineers who use these techniques in production. Table of Contents PART 1 - WORDY MACHINES Packets of thought (NLP overview) Build your vocabulary (word tokenization) Math with words (TF-IDF vectors) Finding meaning in word counts (semantic analysis) PART 2 - DEEPER LEARNING (NEURAL NETWORKS) Baby steps with neural networks (perceptrons and backpropagation) Reasoning with word vectors (Word2vec) Getting words in order with convolutional neural networks (CNNs) Loopy (recurrent) neural networks (RNNs) Improving retention with long short-term memory networks Sequence-to-sequence models and attention PART 3 - GETTING REAL (REAL-WORLD NLP CHALLENGES) Information extraction (named entity extraction and question answering) Getting chatty (dialog engines) Scaling up (optimization, parallelization, and batch processing)