Center for Analysis and Design of Intelligent Agents public:t-720-atai:atai-22

public:t-720-atai:atai-22:agents_and_control

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

T-720-ATAI-2022 Main Links to Lecture Notes CONTROL What is a Controller? Abstract Controller An abstraction of a controller: A set of processes P that can receive an input, i_t~in~I, produced by and selected from a task-environment, current state S, at least one goal G (implicit or explicit - see table below) and output o_t~in~O in the form of atomic actions (selected from a set of atomic possible outputs O), that (in the lim…

public:t-720-atai:atai-22:ai_architectures

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

T-720-ATAI-2022 Main Links to Lecture Notes SYMBOLS, MODELS, CAUSALITY: AI Architectures Refresher: System Architecture What it is In CS: the organization of the software that implements a system. In AI: The total system that has direct and independent control of the behavior of an Agent via its sensors and effectors.

public:t-720-atai:atai-22:causation

Anonymous (anonymous@undisclosed.example.com) — 2025-04-27T11:39:41+00:00

T-720-ATAI-2022 Main Links to Lecture Notes SYMBOLS, MODELS, CAUSALITY: Causation, Probabilities & More Experience-Based Learning What It Is Learning is the acquisition of knowledge for particular purposes. When this acquisition happens via interaction with an environment it is experience-based.

public:t-720-atai:atai-22:engineering_assignment_1

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

T-720-ATAI-2022 Main ATAI-21 Reykjavik University Engineering Assignment 1: Learning Aim: This assignment is meant to give you a better insight into deep reinforcement learning and its difference to cumulative and life-long learning on the example of human learning.

public:t-720-atai:atai-22:engineering_assignment_2

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

ATAI-22 Reykjavik University Engineering Assignment 2: Knowledge Transfer in OpenNARS for Applications (ONA) The aim of this assignment is to introduce you to a general-purpose AI system, OpenNARS-for-Applications (ONA), and to familiarize you with how ONA transfers and generalizes knowledge.

public:t-720-atai:atai-22:evaluation

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

T-720-ATAI-2022 Main Learning / Evaluation Evaluation of Intelligent Systems The Challenge of Evaluating Intelligence Without Evaluation... ...there can be no comparison. Without comparison there can be no indication of direction. Without direction there can be no systematic scientific (or otherwise) effort to deepen understanding.

public:t-720-atai:atai-22:example_questions_2022

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

Final Exam T-720-ATAI-2021 The final exam will be a 3-hour open-book on-line exam (Canvas). Questions will focus on your understanding of the material that has been presented in the course and can be found in the assigned readings and lecture notes, with an emphasis on the main concepts and topics and your ability to holistically comprehend these.

public:t-720-atai:atai-22:final_project

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

T-720-ATAI-2022 Main ATAI-22 Reykjavik University Final Project: Aim: The final project aims at giving you a deeper insight into an AGI-aspiring system (i.e. ONA) and its analogy making capabilities. This includes inference of similarities through interaction, as well as negative knowledge transfer.

public:t-720-atai:atai-22:generality

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

T-720-ATAI-2022 Main Links to Lecture Notes CONTROL: Intelligence & Generality Generality What Do You Mean by "Generality"? Flexibility: Breadth of task-environments Enumeration of variety. (By 'variety' we mean the discernibly different states that can be sensed and that make a difference to a controller.)

public:t-720-atai:atai-22:intelligence

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

T-720-ATAI-2022 Main Link to Lecture Notes INTELLIGENCE Intelligence: A Natural Phenomenon Intelligence A phenomenon encountered in nature. Intelligence is a phenomenon with good examples in the natural world, but may have more forms than the examples from nature. The only one that

public:t-720-atai:atai-22:knowledge_representation

Anonymous (anonymous@undisclosed.example.com) — 2024-11-20T12:02:12+00:00

T-720-ATAI-2022 Main Links to Lecture Notes SYMBOLS, MODELS, CAUSALITY: Knowledge Representation Foundational Concepts Data Measurement. Information Data that can be / is used or formatted for a purpose. Knowledge A set of interlinked information that can be used to plan, produce action, and interpret new information.

public:t-720-atai:atai-22:learning

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

T-720-ATAI-2022 Main Learning Terminology & Definitions Key Learning Terms What it is Learning is a process that has the intent of acquiring actionable information, a.k.a. knowledge. Key Features Inherits key features of any process: -

public:t-720-atai:atai-22:learning_outcomes

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

DCS-T-720-ATAI-2022 Main Learning Outcomes DCS-t-720-ATAI-22 After taking the course, diligently attending the classes and doing the assignments, thoroughly reading, and actively participating in discussions, students should be able to: * Identify key challenging research questions related to advanced machine learning and (AML) general machine intelligence (GMI)

public:t-720-atai:atai-22:lecture_notes

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

T-720-ATAI-2022 Main T-720-ATAI-2022 Links to Thórisson's Lecture Notes * W1: INTRODUCTION * Intelligence: The Phenomenon * Sprint W2+W3: WORLDS * Key concepts: Environment, tasks, entities, variables, tests, goals, behaviors * Tasks & Environments * Emergence & Self-Organization * Sprint W4+W5: LEARNING * Key concepts:

public:t-720-atai:atai-22:main

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

T-720-ATAI, ADVANCED TOPICS IN ARTIFICIAL INTELLIGENCE, Fall 2022 —The Year COVID Gets Eradicated— OVERVIEW See last year's course here Organization of this course See Canvas For Up-To-Date Information, Notifications, Links to Lecture Notes Instructor: Kristinn R. Thórisson

public:t-720-atai:atai-22:methodologies

Anonymous (anonymous@undisclosed.example.com) — 2024-10-29T00:19:20+00:00

T-720-ATAI-2022 Main Links to Lecture Notes UNDERSTANDING: Methodologies Methodology First Things First: What is a Methodology? What it is The methods - tools and techniques - we use to study a phenomenon. Examples - Comparative experiments (for the answers we want Nature to ultimately give).

public:t-720-atai:atai-22:readings

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

DCS-T-720-ATAI-2022 Main T-720-ATAI-2022 Readings & Study Material Readings README (Do not skip!) INTELLIGENCE: THE PHENOMENON The Human Animal [ 9,10 ] What is intelligence? How do experts talk about it? What has been uncovered? What uniquely separates the phenomenon of intelligence from other similar phenomena in the world?

public:t-720-atai:atai-22:self-organization

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

T-720-ATAI-2022 Main Lecture Notes 2022 Complexity & Emergence Introduction What is Complexity? Complexity characterises the behaviour of a system or model whose components interact in multiple ways and follow local rules, leading to nonlinearity, randomness, collective dynamics, hierarchy, and emergence.

public:t-720-atai:atai-22:self-x

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

T-720-ATAI-2022 Main Links to Lecture Notes CONTROL: Self-X, Predictability, Reliability, & Trustworthiness Autonomy What It Is Autonomy is a key feature of intelligence - the ability of a system to “act on its own”. Autonomous-X is anything that “autonomy” is relevant for or applies to in a system's operation.

public:t-720-atai:atai-22:task-environment

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

T-720-ATAI-2022 Main Lecture Notes 2022 WORLDS "The World" What is it? A set of constraints on what is and isn't possible. We perceive the physical world through sensors. Sensors are physical Our sensors are made from the same stuff that they perceive. Descartes

public:t-720-atai:atai-22:teaching

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

T-720-ATAI-2022 Main T-720-ATAI-2022 Learning / Teaching The Pedagogical Pentagon: A Framework for (Artificial) Pedagogy What is Needed We need a universal theory of learning -- and in fact of teaching, training, task-environments, and evaluation. Anything short of having complete theories for all of these means that experimentation, exploration, and blind search are the only ways to answer questions about performance, curriculum design, training requirements, etc., and for whi…

public:t-720-atai:atai-22:thecourse

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

T-720-ATAI-2022 Main Links to Lecture Notes Course Overview Organization The bulk of the course is built up of 5 “sprints” on 5 key topics, each covering 2 weeks. The general organization of these is such: - The first week involves presentation of the sprint's topic(s), assignments, and other related things.

public:t-720-atai:atai-22:understanding

Anonymous (anonymous@undisclosed.example.com) — 2024-04-29T13:33:28+00:00

T-720-ATAI-2022 Main Links to Lecture Notes UNDERSTANDING: Understanding, Curiosity, Creativity Curiosity What is Curiosity? What It Is The tendency of a learner to seek out novel inputs that may not have any relevance to its currently active goals. Why It Matters