Stuart Russell
(33 articles)
Task Environment
Setting or context within which an intelligent agent operates and attempts to achieve its objectives.
Generality: 760
Heuristic Search Techniques
Methods used in AI to find solutions or make decisions more efficiently by using rules of thumb or informed guesses to guide the search process.
Generality: 878
Autonomous Agents
Systems capable of independent action in dynamic, unpredictable environments to achieve designated objectives.
Generality: 875
Agent
System capable of perceiving its environment through sensors and acting upon that environment to achieve specific goals.
Generality: 790
Intelligence Explosion
Hypothetical scenario where an AI system rapidly improves its own capabilities and intelligence, leading to a superintelligent AI far surpassing human intelligence.
Generality: 575
Inference
Process by which a trained neural network applies learned patterns to new, unseen data to make predictions or decisions.
Generality: 861
Recursive Self-Improvement
Process by which an AI system iteratively improves itself, enhancing its intelligence and capabilities without human intervention.
Generality: 790
Hierarchical Planning
Approach to solving complex problems by breaking them down into more manageable sub-problems, organizing these into a hierarchy.
Generality: 845
CSPs
Constraint Satisfaction Problems
Constraint Satisfaction Problems
Mathematical problems defined by a set of variables, a domain of values for each variable, and a set of constraints specifying allowable combinations of values.
Generality: 800
Reasoning System
Software entities designed to emulate human reasoning processes by drawing logical inferences from available data or known facts.
Generality: 775
Probabilistic Inferencing
A technique in AI focused on drawing conclusions based on the probability of different outcomes, given partial or uncertain information.
Generality: 870
Bayesian Network
Graphical model that represents probabilistic relationships among variables using directed acyclic graphs (DAGs).
Generality: 820
Artificial Curiosity
Algorithmic mechanism in AI that motivates the system's behavior to learn inquisitively and explore unfamiliar environments.
Generality: 625
Agent-to-Agent Interaction
Communication and cooperation between autonomous agents within a multi-agent system to achieve individual or collective goals.
Generality: 735
AI Effect
Phenomenon where once an AI system can perform a task previously thought to require human intelligence, the task is no longer considered to be a benchmark for intelligence.
Generality: 770
Fast Takeoff
Rapid transition from human-level to superintelligent AI, occurring in a very short period of time.
Generality: 504
Superintelligence
A form of AI that surpasses the cognitive performance of humans in virtually all domains of interest, including creativity, general wisdom, and problem-solving.
Generality: 850
Control Problem
Challenge of ensuring that highly advanced AI systems act in alignment with human values and intentions.
Generality: 845
IRL
Inverse Reinforcement Learning
Inverse Reinforcement Learning
Technique in which an algorithm learns the underlying reward function of an environment based on observed behavior from an agent, essentially inferring the goals an agent is trying to achieve.
Generality: 658
AI Safety
Field of research aimed at ensuring AI technologies are beneficial and do not pose harm to humanity.
Generality: 870
Catastrophic Risk
The potential for AI systems to cause large-scale harm or failure due to unforeseen vulnerabilities, operational errors, or misuse.
Generality: 775
HITL
Human-in-the-Loop
Human-in-the-Loop
Integration of human judgment into AI systems to improve or guide the decision-making process.
Generality: 665
AI Failure Modes
Diverse scenarios where AI systems do not perform as expected or generate unintended consequences.
Generality: 714
Alignment
Process of ensuring that an AI system's goals and behaviors are consistent with human values and ethics.
Generality: 790
Ethical AI
Practice of creating AI technologies that follow clearly defined ethical guidelines and principles to benefit society while minimizing harm.
Generality: 830
AI Governance
Set of policies, principles, and practices that guide the ethical development, deployment, and regulation of artificial intelligence technologies.
Generality: 860
Embodied AI
Integration of AI into physical entities, enabling these systems to interact with the real world through sensory inputs and actions.
Generality: 780
Responsible AI
Application of AI in a manner that is transparent, unbiased, and respects user privacy and value.
Generality: 815
Hybrid AI
Combines symbolic AI (rule-based systems) and sub-symbolic AI (machine learning) approaches to leverage the strengths of both for more versatile and explainable AI systems.
Generality: 820
Autonomous Reasoning
Capacity of AI systems to make independent decisions or draw conclusions based on logic or data without human intervention.
Generality: 850
AMI
Advanced Machine Intelligence
Advanced Machine Intelligence
Refers to high-level AI systems possessing the capability to perform complex cognitive tasks with or without human-like reasoning.
Generality: 873
Agentic AI Systems
Advanced AI capable of making decisions and taking actions autonomously to achieve specific goals, embodying characteristics of agency and decision-making usually associated with humans or animals.
Generality: 775
P
Doom
Doom
Probability of an existential catastrophe, often discussed within the context of AI safety and risk assessment.
Generality: 550