Computational Curiosity (A Book Draft)
This book discusses computational curiosity, from the psychology of curiosity to the computational models of curiosity, and then showcases several interesting applications of computational curiosity. A brief overview of the book is given as follows. Chapter 1 discusses the underpinnings of curiosity in human beings, including the major categories of curiosity, curiosity-related emotions and behaviors, and the benefits of curiosity. Chapter 2 reviews the arousal theories of curiosity in psychology and summarizes a general two-step process model for computational curiosity. Base on the perspective of the two-step process model, Chapter 3 reviews and analyzes some of the traditional computational models of curiosity. Chapter 4 introduces a novel generic computational model of curiosity, which is developed based on the arousal theories of curiosity. After the discussion of computational models of curiosity, we outline the important applications where computational curiosity may bring significant impacts in Chapter 5. Chapter 6 discusses the application of the generic computational model of curiosity in a machine learning framework. Chapter 7 discusses the application of the generic computational model of curiosity in a recommender system. In Chapter 8 and Chapter 9, the generic computational model of curiosity is studied in two types of pedagogical agents. In Chapter 8, a curious peer learner is studied. It is a non-player character that aims to provide a believable virtual learning environment for users. In Chapter 9, a curious learning companion is studied. It aims to enhance users' learning experience through providing meaningful interactions with them. Chapter 10 discusses open questions in the research field of computation curiosity.
Code (0)
등록된 구현이 없습니다.
Tasks
Recommendation SystemsSimilar Papers 제목 키워드 기반
Supporting Qualitative Analysis with Large Language Models: Combining Codebook with GPT-3 for Deductive Coding
Qualitative analysis of textual contents unpacks rich and valuable information by assigning labels to the data. However, this process is often labor-intensive, particularly when working with large datasets. While recent …
Prompt LearningFive Properties of Specific Curiosity You Didn't Know Curious Machines Should Have
Curiosity for machine agents has been a focus of lively research activity. The study of human and animal curiosity, particularly specific curiosity, has unearthed several properties that would offer important benefits fo…
Decision Makingreinforcement-learningReinforcement Learning (RL)Computational Theories of Curiosity-Driven Learning
What are the functions of curiosity? What are the mechanisms of curiosity-driven learning? We approach these questions about the living using concepts and tools from machine learning and developmental robotics. We argue …
BIG-bench Machine LearningLifelong learningThe growth and form of knowledge networks by kinesthetic curiosity
Throughout life, we might seek a calling, companions, skills, entertainment, truth, self-knowledge, beauty, and edification. The practice of curiosity can be viewed as an extended and open-ended search for valuable infor…
FormModel-based Reinforcement LearningPhilosophyNeural Machine Translation
Draft of textbook chapter on neural machine translation. a comprehensive treatment of the topic, ranging from introduction to neural networks, computation graphs, description of the currently dominant attentional sequenc…
Machine TranslationTranslation